apraga/org - Change TF57F5BAMREE7DHNBGN6SWNMMHU5A27DP23KCLHM74BGOQBOKLAQC

Saving bisonex

Created by Alexis Praga on July 4, 2023

TF57F5BAMREE7DHNBGN6SWNMMHU5A27DP23KCLHM74BGOQBOKLAQC

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Change contents

Replacement in projects/bisonex.org at line 4 [4.35]

B:BD[3.8221] → [2.29:8221]

ED: [2023-06-14 Wed 22:35]
***** DONE compatibilité hg38
CLOSED: [2023-06-14 Wed 22:35]
**** TODO cache vep
SCHEDULED: <2023-07-03 Mon>
**** TODO GIAB :giab:
#+begin_quote
We performed liftover using the GATK release 4.1.9 LiftoverVcf (Picard Version 2.23.3) tool with the default parameters. This successfully lifts over variants that map exactly from GRCh38 to T2T-CHM13v2.0 but does not recover variants with swapped reference and alternative alleles. To recover variants with swapped reference/alternative alleles, we ran LiftoverVCF again, with the RECOVER_SWAPPED_REF_ALT flag. Notably, this feature does not recover multiallelic variants, so to recover these variants, we first separated them into multiple biallelic variants, performed liftover using the RECOVER_SWAPPED_REF_ALT tag, and converted them back to their multiallelic representations.
#+end_quote
***** TODO Liftovervcf avec valeur par défaut
SCHEDULED: <2023-06-30 Fri>
HG002 : il manque la moitié des valeurs
hg001
[apraga@mesointeractive b946d0e6bc8d0f220eb1ad1649c20d]$ less HG004_GRCh38_1_22_v4.2.1_benchmark.vcf.lifted.vcf.gz
[apraga@mesointeractive b946d0e6bc8d0f220eb1ad1649c20d]$ zgrep -c '^chr' HG004_GRCh38_1_22_v4.2.1_benchmark.vcf.lifted.vcf.gz
2168972
[apraga@mesointeractive b946d0e6bc8d0f220eb1ad1649c20d]$ zgrep -c '^chr' HG004_GRCh38_1_22_v4.2.1_benchmark.vcf.unlifted.vcf.gz
1862374
[apraga@mesointeractive b946d0e6bc8d0f220eb1ad1649c20d]$ zgrep -c '^chr' HG004_GRCh38_1_22_v4.2.1_benchmark.vcf.gz
4031346
***** TODO liftover bed
SCHEDULED: <2023-06-30 Fri>
***** TODO Liftovervcf avec variant échangé référence/alternative ?
*** HOLD Processing bases de données
**** DONE dbSNP common
**** DONE Seulement les ID dans dbSNP common !
CLOSED: [2022-11-19 Sat 21:42]
172G au lieu de 253M...
**** HOLD common dbSNP not clinvar patho
***** DONE Conclusion partielle
CLOSED: [2022-12-12 Mon 22:25]
- vcfeval : prometteur mais n'arrive pas à traiter toutes les régions
- isec : trop de problèmes avec
- classif clinvar directement dans dbSNP: le plus simple
  Et ça permet de rattraper quelques erreurs dans le script d'Alexis
***** KILL Utiliser directement le numéro dbSNP dans clinvar ? Non
CLOSED: [2022-11-20 Sun 19:51]
Ex: chr20
#+begin_src sh :dir ~/code/bisonex/test_isec
bcftools query -f 'rs%INFO/RS \n' -i 'INFO/RS != "." & INFO/CLNSIG="Pathogenic"' clinvar_chr20.vcf.gz | sort > ID_clinvar_patho.txt
bcftools query -f '%ID\n' dbSNP_common_chr20.vcf.gz | sort > ID_of_common_snp.txt
comm -23 ID_of_common_snp.txt ID_clinvar_patho.txt > ID_of_common_snp_not_clinvar_patho.txt
wc -l ID_of_common_snp_not_clinvar_patho.txt
# sort ID
#+end_src
#+RESULTS:
: 518846 ID_of_common_snp_not_clinvar_patho.txt
Version d'alexis
#+begin_src sh :dir ~/code/bisonex/test_isec
snp=dbSNP_common_chr20.vcf.gz
clinvar=clinvar_chr20_notremapped.vcf.gz
python ../script/pythonScript/clinvar_sbSNP.py \
    --clinvar $clinvar \
    --chrm_name_table ../database/RefSeq/refseq_to_number_only_consensual.txt \
    --dbSNP $snp --output prod.txt
wc -l prod.txt
zgrep '^NC' dbSNP_common_chr20.vcf.gz | wc -l
#+end_src
#+RESULTS:
| 518832 | prod.txt |
| 518846 |          |
***** KILL classification clinvar codée dbSNP ?
CLOSED: [2022-12-04 Sun 14:38]
Sur le chromosome 20
*Attention* CLNSIG a plusieurs champs (séparé par une virgule)
On y accède avec INFO/CLNSIG[*]
Ensuite, chaque item peut avoir plusieurs haploïdie (séparé par un |). IL faut donc utiliser une regexp
NB: *ne pas mettre la condition* dans une variable !!
Pour avoir les clinvar patho, on veut 5 mais pas 255 (= autre) pour la classification !`
Il faut également les likely patho et conflicting
#+begin_src sh :dir ~/code/bisonex/test_isec
bcftools query -f '%INFO/CLNSIG\n' dbSNP_common_chr20.vcf.gz -i \
'INFO/CLNSIG[*]~"^5|" | INFO/CLNSIG[*]=="5" | INFO/CLNSIG[*]~"|5" | INFO/CLNSIG[*]~"^4|" | INFO/CLNSIG[*]=="4" | INFO/CLNSIG[*]~"|4" | INFO/CLNSIG[*]~"^12|" | INFO/CLNSIG[*]=="12" | INFO/CLNSIG[*]~"|12"' | sort
#+end_src
#+RESULTS:
| . |  . | 12 |    |   |   |   |   |   |   |   |
| . | 12 |  0 |  2 |   |   |   |   |   |   |   |
| 2 |  3 |  2 |  2 | 2 | 5 | . |   |   |   |   |
| . |  2 |  3 |  2 | 2 | 4 |   |   |   |   |   |
| . |  . |  3 | 12 | 3 |   |   |   |   |   |   |
| . |  5 |  2 |  . |   |   |   |   |   |   |   |
| . |  . |  . |  5 | 2 | 2 |   |   |   |   |   |
| . |  9 |  9 |  9 | 5 | 5 | 2 | 3 | 2 | 3 | 2 |
Si on les exclut :
#+begin_src sh :dir ~/code/bisonex/test_isec
bcftools query -f '%ID\n' dbSNP_common_chr20.vcf.gz -e \
'INFO/CLNSIG[*]~"^5|" | INFO/CLNSIG[*]=="5" | INFO/CLNSIG[*]~"|5" | INFO/CLNSIG[*]~"4" | INFO/CLNSIG[*]~"12"' | sort | uniq > common-notpatho.txt
#+end_src
#+RESULTS:
 #+begin_src sh :dir ~/code/bisonex/test_isec
snp=dbSNP_common_chr20.vcf.gz
clinvar=clinvar_chr20_notremapped.vcf.gz
python ../script/pythonScript/clinvar_sbSNP.py \
    --clinvar $clinvar \
    --chrm_name_table ../database/RefSeq/refseq_to_number_only_consensual.txt \
    --dbSNP $snp --output tmp.txt
sort tmp.txt | uniq > common-notpatho-alexis.txt
wc -l common-notpatho-alexis.txt
 #+end_src
 #+RESULTS:
 : 518832 common-notpatho-alexis.txt
On en a 6 de plus que la version d'Alexis mais quelques différences
Ceux d'Alexis qui manquent:
#+begin_src sh :dir ~/code/bisonex/test_isec
comm -23 common-notpatho-alexis.txt common-notpatho.txt > alexis-only.txt
cat alexis-only.txt
#+end_src
#+RESULTS:
| rs1064039  |
| rs3833341  |
| rs73598374 |
On les teste dans clinvar et dbSNP
#+begin_src sh :dir ~/code/bisonex/test_isec
bcftools query -f '%POS %REF %ALT %INFO/CLNSIG\n' -i 'ID=@alexis-only.txt' dbSNP_common_chr20.vcf.gz
bcftools query -f '%POS\n' -i 'ID=@alexis-only.txt' dbSNP_common_chr20.vcf.gz > alexis-only-pos.txt
while read  -r line; do
bcftools query -f '%POS %REF %ALT %INFO/CLNSIG\n' -i 'POS='$line clinvar_chr20.vcf.gz
done < alexis-only-pos.txt
# bcftools query -f '%POS %REF %ALT %INFO/CLNSIG\n' -i 'POS=23637790' clinvar_chr20.vcf.gz
#+end_src
#+RESULTS:
|   764018 | A | ACAGGTCAAT,ACAGGT | .,5     | 2,. |   |
| 23637790 | C | G,T               | .,.,12  |     |   |
| 44651586 | C | A,G,T             | .,.,.,5 |   2 | 2 |
|   764018 | A | ACAGGTCAAT        | Benign  |     |   |
| 23637790 | C | T                 | Benign  |     |   |
| 44651586 | C | T                 | Benign  |     |   |
On a donc une discordance entre clinvar et dbSNP.
On dirait qu'ils ont mal fait l'intersection avec clinvar.
Par exemple https://www.ncbi.nlm.nih.gov/snp/rs3833341#clinical_significance
Tu as l'impression qu'il y a un 1 clinvar bénin et 1 patho.
En cherchant par NM, tu vois qu'il est bénin sur clinvar car il y a d'autres soumissions ! https://www.ncbi.nlm.nih.gov/clinvar/variation/262235/
Confirmation sur nos bases de données :
$ bcftools query -f '%POS %REF %ALT %INFO/CLNSIG\n' -i 'POS=764018' dbSNP_common_chr20.vcf.gz
764018 A ACAGGTCAAT,ACAGGT .,5|2,.
$ bcftools query -f '%POS %REF %ALT %INFO/CLNSIG\n' -i 'POS=764018' clinvar_chr20.vcf.gz
764018 A ACAGGTCAAT Benign
***** KILL Corriger script alexi
CLOSED: [2022-12-04 Sun 13:03]
Gère clinvar patho, probablement patho ou conflicting !
***** HOLD Rtg tools
****** Test
1. Générer SDf file
   #+begin_src sh
rtg format genomeRef.fna  -o genomeRef.sdf
   #+end_src
2. Pour les bases de donnés, il faut l'option --sample ALT sinon on a
 #+begin_src
$ rtg vcfeval -b dbSNP_common.vcf.gz -c clinvar.vcf.gz -o test -t genomeRef.sdf/^C
VCF header does not contain a FORMAT field named GQ
Error: Record did not contain enough samples: NC_000001.11	10001	rs1570391677	A,C	.	PASS	RS=1570391677;dbSNPBuildID=154;SSR=0;PSEUDOGENEINFO=DDX11L1:100287102;VC=SNV;R5;GNO;FREQ=KOREAN:0.9891,0.0109,.|SGDP_PRJ:0,1,.|dbGaP_PopFreq:1,.,0;COMMON
 #+end_src
 Essai intersection clinvar (patho ou non) dbSNP
   - faux négatif = dbSNP common qui ne sont pas dans clinvar
   - faux positif = clinvar qui ne sont pas dbSNP common
   - vrai positif = clinvar qui sont dans dbSNP common
   - vrai positif baseline = dbSNP common qui sont dans cl

[3.8221]

[2.8221]

ED: [2023-06-14 Wed 22:35]
***** DONE compatibilité hg38
CLOSED: [2023-06-14 Wed 22:35]
**** TODO cache vep
SCHEDULED: <2023-07-10 Mon>
*** HOLD Processing bases de données
**** DONE dbSNP common
**** DONE Seulement les ID dans dbSNP common !
CLOSED: [2022-11-19 Sat 21:42]
172G au lieu de 253M...
**** HOLD common dbSNP not clinvar patho
***** DONE Conclusion partielle
CLOSED: [2022-12-12 Mon 22:25]
- vcfeval : prometteur mais n'arrive pas à traiter toutes les régions
- isec : trop de problèmes avec
- classif clinvar directement dans dbSNP: le plus simple
  Et ça permet de rattraper quelques erreurs dans le script d'Alexis
***** KILL Utiliser directement le numéro dbSNP dans clinvar ? Non
CLOSED: [2022-11-20 Sun 19:51]
Ex: chr20
#+begin_src sh :dir ~/code/bisonex/test_isec
bcftools query -f 'rs%INFO/RS \n' -i 'INFO/RS != "." & INFO/CLNSIG="Pathogenic"' clinvar_chr20.vcf.gz | sort > ID_clinvar_patho.txt
bcftools query -f '%ID\n' dbSNP_common_chr20.vcf.gz | sort > ID_of_common_snp.txt
comm -23 ID_of_common_snp.txt ID_clinvar_patho.txt > ID_of_common_snp_not_clinvar_patho.txt
wc -l ID_of_common_snp_not_clinvar_patho.txt
# sort ID
#+end_src
#+RESULTS:
: 518846 ID_of_common_snp_not_clinvar_patho.txt
Version d'alexis
#+begin_src sh :dir ~/code/bisonex/test_isec
snp=dbSNP_common_chr20.vcf.gz
clinvar=clinvar_chr20_notremapped.vcf.gz
python ../script/pythonScript/clinvar_sbSNP.py \
    --clinvar $clinvar \
    --chrm_name_table ../database/RefSeq/refseq_to_number_only_consensual.txt \
    --dbSNP $snp --output prod.txt
wc -l prod.txt
zgrep '^NC' dbSNP_common_chr20.vcf.gz | wc -l
#+end_src
#+RESULTS:
| 518832 | prod.txt |
| 518846 |          |
***** KILL classification clinvar codée dbSNP ?
CLOSED: [2022-12-04 Sun 14:38]
Sur le chromosome 20
*Attention* CLNSIG a plusieurs champs (séparé par une virgule)
On y accède avec INFO/CLNSIG[*]
Ensuite, chaque item peut avoir plusieurs haploïdie (séparé par un |). IL faut donc utiliser une regexp
NB: *ne pas mettre la condition* dans une variable !!
Pour avoir les clinvar patho, on veut 5 mais pas 255 (= autre) pour la classification !`
Il faut également les likely patho et conflicting
#+begin_src sh :dir ~/code/bisonex/test_isec
bcftools query -f '%INFO/CLNSIG\n' dbSNP_common_chr20.vcf.gz -i \
'INFO/CLNSIG[*]~"^5|" | INFO/CLNSIG[*]=="5" | INFO/CLNSIG[*]~"|5" | INFO/CLNSIG[*]~"^4|" | INFO/CLNSIG[*]=="4" | INFO/CLNSIG[*]~"|4" | INFO/CLNSIG[*]~"^12|" | INFO/CLNSIG[*]=="12" | INFO/CLNSIG[*]~"|12"' | sort
#+end_src
#+RESULTS:
| . |  . | 12 |    |   |   |   |   |   |   |   |
| . | 12 |  0 |  2 |   |   |   |   |   |   |   |
| 2 |  3 |  2 |  2 | 2 | 5 | . |   |   |   |   |
| . |  2 |  3 |  2 | 2 | 4 |   |   |   |   |   |
| . |  . |  3 | 12 | 3 |   |   |   |   |   |   |
| . |  5 |  2 |  . |   |   |   |   |   |   |   |
| . |  . |  . |  5 | 2 | 2 |   |   |   |   |   |
| . |  9 |  9 |  9 | 5 | 5 | 2 | 3 | 2 | 3 | 2 |
Si on les exclut :
#+begin_src sh :dir ~/code/bisonex/test_isec
bcftools query -f '%ID\n' dbSNP_common_chr20.vcf.gz -e \
'INFO/CLNSIG[*]~"^5|" | INFO/CLNSIG[*]=="5" | INFO/CLNSIG[*]~"|5" | INFO/CLNSIG[*]~"4" | INFO/CLNSIG[*]~"12"' | sort | uniq > common-notpatho.txt
#+end_src
#+RESULTS:
 #+begin_src sh :dir ~/code/bisonex/test_isec
snp=dbSNP_common_chr20.vcf.gz
clinvar=clinvar_chr20_notremapped.vcf.gz
python ../script/pythonScript/clinvar_sbSNP.py \
    --clinvar $clinvar \
    --chrm_name_table ../database/RefSeq/refseq_to_number_only_consensual.txt \
    --dbSNP $snp --output tmp.txt
sort tmp.txt | uniq > common-notpatho-alexis.txt
wc -l common-notpatho-alexis.txt
 #+end_src
 #+RESULTS:
 : 518832 common-notpatho-alexis.txt
On en a 6 de plus que la version d'Alexis mais quelques différences
Ceux d'Alexis qui manquent:
#+begin_src sh :dir ~/code/bisonex/test_isec
comm -23 common-notpatho-alexis.txt common-notpatho.txt > alexis-only.txt
cat alexis-only.txt
#+end_src
#+RESULTS:
| rs1064039  |
| rs3833341  |
| rs73598374 |
On les teste dans clinvar et dbSNP
#+begin_src sh :dir ~/code/bisonex/test_isec
bcftools query -f '%POS %REF %ALT %INFO/CLNSIG\n' -i 'ID=@alexis-only.txt' dbSNP_common_chr20.vcf.gz
bcftools query -f '%POS\n' -i 'ID=@alexis-only.txt' dbSNP_common_chr20.vcf.gz > alexis-only-pos.txt
while read  -r line; do
bcftools query -f '%POS %REF %ALT %INFO/CLNSIG\n' -i 'POS='$line clinvar_chr20.vcf.gz
done < alexis-only-pos.txt
# bcftools query -f '%POS %REF %ALT %INFO/CLNSIG\n' -i 'POS=23637790' clinvar_chr20.vcf.gz
#+end_src
#+RESULTS:
|   764018 | A | ACAGGTCAAT,ACAGGT | .,5     | 2,. |   |
| 23637790 | C | G,T               | .,.,12  |     |   |
| 44651586 | C | A,G,T             | .,.,.,5 |   2 | 2 |
|   764018 | A | ACAGGTCAAT        | Benign  |     |   |
| 23637790 | C | T                 | Benign  |     |   |
| 44651586 | C | T                 | Benign  |     |   |
On a donc une discordance entre clinvar et dbSNP.
On dirait qu'ils ont mal fait l'intersection avec clinvar.
Par exemple https://www.ncbi.nlm.nih.gov/snp/rs3833341#clinical_significance
Tu as l'impression qu'il y a un 1 clinvar bénin et 1 patho.
En cherchant par NM, tu vois qu'il est bénin sur clinvar car il y a d'autres soumissions ! https://www.ncbi.nlm.nih.gov/clinvar/variation/262235/
Confirmation sur nos bases de données :
$ bcftools query -f '%POS %REF %ALT %INFO/CLNSIG\n' -i 'POS=764018' dbSNP_common_chr20.vcf.gz
764018 A ACAGGTCAAT,ACAGGT .,5|2,.
$ bcftools query -f '%POS %REF %ALT %INFO/CLNSIG\n' -i 'POS=764018' clinvar_chr20.vcf.gz
764018 A ACAGGTCAAT Benign
***** KILL Corriger script alexi
CLOSED: [2022-12-04 Sun 13:03]
Gère clinvar patho, probablement patho ou conflicting !
***** HOLD Rtg tools
****** Test
1. Générer SDf file
   #+begin_src sh
rtg format genomeRef.fna  -o genomeRef.sdf
   #+end_src
2. Pour les bases de donnés, il faut l'option --sample ALT sinon on a
 #+begin_src
$ rtg vcfeval -b dbSNP_common.vcf.gz -c clinvar.vcf.gz -o test -t genomeRef.sdf/^C
VCF header does not contain a FORMAT field named GQ
Error: Record did not contain enough samples: NC_000001.11	10001	rs1570391677	A,C	.	PASS	RS=1570391677;dbSNPBuildID=154;SSR=0;PSEUDOGENEINFO=DDX11L1:100287102;VC=SNV;R5;GNO;FREQ=KOREAN:0.9891,0.0109,.|SGDP_PRJ:0,1,.|dbGaP_PopFreq:1,.,0;COMMON
 #+end_src
 Essai intersection clinvar (patho ou non) dbSNP
   - faux négatif = dbSNP common qui ne sont pas dans clinvar
   - faux positif = clinvar qui ne sont pas dbSNP common
   - vrai positif = clinvar qui sont dans dbSNP common
   - vrai positif baseline = dbSNP common qui sont dans cl

Replacement in projects/bisonex.org at line 8 [4.35]

B:BD[3.14909] → [3.14909:16414]

B:BD[3.16414] → [2.9727:16414]

L    ALL       525466    491355     34111      1156702     57724     605307   9384  25027       0.935084          0.895313        0.523304         0.914766
INDEL   PASS       525466    491355     34111      1156702     57724     605307   9384  25027       0.935084          0.895313        0.523304         0.914766
  SNP    ALL      3365115   3358399      6716      5666020     21995    2284364   4194   1125       0.998004          0.993496        0.403169         0.995745
  SNP   PASS      3365115   3358399      6716      5666020     21995    2284364   4194   1125       0.998004          0.993496        0.403169         0.995745
 TRUTH.TOTAL.TiTv_ratio  QUERY.TOTAL.TiTv_ratio  TRUTH.TOTAL.het_hom_ratio  QUERY.TOTAL.het_hom_ratio
                    NaN                     NaN                   1.528276                   2.752637
                    NaN                     NaN                   1.528276                   2.752637
               2.100129                1.473519                   1.581196                   1.795603
               2.100129                1.473519                   1.581196                   1.795603
***** KILL Avec python2
CLOSED: [2023-02-17 Fri 19:25]
****** KILL avec nix
CLOSED: [2023-02-17 Fri 19:25]
conda create -n python2 python=2.7 anaconda
****** KILL avec conda
CLOSED: [2023-02-17 Fri 19:25]
******* Gentoo: regex_error sur test...
Ok avec bash !
#+begin_src
anaconda3/bin/conda create --name py2 python=2.7
conda activate
 py2
conda install -c bioconda hap.py
#+end_src
******** Faire tourner les tests.
Il faut remplace bin/test_haplotypes par test_haplotypes dans src/sh/run_tests.sh
#+begin_src sh
 HGREF=../genome/GRCh38/GCA_000001405.15_GRCh38_no_alt_analysis_set.fasta HCDIR=~/anaconda3/envs/py2/bin bash src/sh/run_tests.sh
#+end_src
Echec:
test_haplotypes: /opt/conda/conda-bld/work/hap.py-0.3.7/src/c++/lib/tools/Fasta.cpp:81: MMappedFastaFile::MMappedFastaFile(const string&): Assertion `fd != -1' failed.
unknown location(0): fatal error in "testVariantPrimitiveSplitter": signal: SIGABRT (application abort requested)
/opt/conda/conda-bld/work/hap.py-0.3.7/src/c++/test/test_align.cpp(298): last checkpoint
******** Chr21
HGREF=../genome/GRCh38/GCA_000001405.15_GRCh38_no_alt_analysis_set.fasta hap.py        example/happy/PG_NA12878_chr21.vcf.gz       example/happy/NA12878_chr21.vcf.gz       -f example/happy/PG_Conf_chr21.bed.gz       -o test
******* Helios
échec
** TODO T2T :T2T:
Toutes les ressourcs sont décrites ici
https://github.com/marbl/CHM13
Détails sur le pipeline
https://genome.ucsc.edu/cgi-bin/hgTrackUi?db=hub_3267197_GCA_009914755.4&c=CP068277.2&g=hub_3267197_hgLiftOver
*** DONE Alignement
CLOSED: [2023-06-26 Mon 19:42]
NXF_OPTS=-D"user.name=${USER}" nextflow run main.nf -profile standard,helios  --input="/Work/Groups/bisonex/data/giab/*_R{1,2}_001.fastq.gz" --id=NA12878-T2T -bg
SCHEDULED: <2023-06-14 Wed>
*** DONE Haplotypecaller
CLOSED: [2023-06-26 Mon 19:42] SCHEDULED: <2023-06-15 Thu>
*** TODO Filtres
SCHEDULED: <2023-07-03 Mon>
*** Liftover pipelines
:PROPERTIES:
:ID:       d2280207-3f65-4a31-a291-41fa9a9658c2
:END:
Contient les chain files
** TODO Indicateurs qualité
SCHEDULED: <2023-07-07 Fri>
*** Idée
Raredisease:
- FastQC : nombreuses statistiques. Non disponible Nix
- Mosdepth : calcule la profondeur (2x plus rapide que samtools depth). Nix
- MultiQC : fusionne juste les résultats des analyses. Non disponible nix
- Picard's CollectMutipleMetrics, CollectHsMetrics, and CollectWgsMetrics
- Qualimap : alternative fastqc ? Non disponible nix
- Sentieon's WgsMetricsAlgo : propriétaire
- TIDDIT's cov : TIDIT = remaninement chromosomique
Sarek:
- alignment statistics : samtools stats, mosdepth
- QC : MultiQC
MultiQC : non disponible Nix
** TODO vérifier si normalisation
SCHEDULED: <2023-07-03 Mon>
** TODO Rajouter vérification hgvs
SCHEDULED: <2023-07-03 Mon>
** DONE Exécution
CLOSED: [2022-09-13 Tue 21:37]
*** KILL test Bionix
*** KILL Implémenter execution avec Nix ?
Voir https://academic.oup.com/gigascience/article/9/11/giaa121/5987272?login=false
pour un exemple.
Probablement plus simple d’utiliser Nix pour gestion de l’environnement et snakemake pour l’exécution
Pas d’accès internet depuis le cluster
*** DONE nextflow
CLOSED: [2022-09-13 Tue 21:37]
**** TODO Bug scheduler SGE
Le job se fait tuer car l'utilisateur n'est pas passé correctement à nextflow
***** DONE Forcer l'utilisateur à l'exécution
CLOSED: [2023-04-01 Sat 17:57]
NXF_OPTS=-D"user.name=alex"
***** DONE Vérifier si le problème persiste avec 22.10.6
CLOSED: [2023-04-01 Sat 18:38] SCHEDULED: <2023-04-01 Sat>
oui
***** KILL Packager l'utilisateur dans le programme ?
Mauvaise idée..
** TODO Preprocessing avec nextflow
*** TODO Map to reference
**** TODO Sample ID dans header
/Work/Users/apraga/bisonex/out/63003856_S135/preprocessing/baserecalibrator
*** DONE Mark duplicate
CLOSED: [2022-10-09 Sun 22:30]
*** DONE Recalibrate base quality score
CLOSED: [2022-10-09 Sun 22:30]
** DONE Variant calling avec Nextflow
CLOSED: [2022-11-19 Sat 21:34]
*** DONE Haplotype caller
CLOSED: [2022-10-09 Sun 22:40]
*** DONE Filter variants
CLOSED: [2022-10-09 Sun 22:40]
*** DONE Filter common snp not clinvar path
CLOSED: [2022-11-07 Mon 23:00]
Voir [[*common dbSNP not clinvar patho][common dbSNP not clinvar patho]]
*** DONE Filter variant only in consensual sequence
CLOSED: [2022-11-08 Tue 22:23]
*** DONE Filter technical variants
CLOSED: [2022-11-19 Sat 21:34]
*** DONE Utilise AVX pour accélerer l'exécution
CLOSED: [2023-04-29 Sat 15:46]
Sans cela, on a l'avertissement
#+begin_quote
17:28:00.720 INFO  PairHMM - OpenMP multi-threaded AVX-accelerated native PairHMM implementation is not supported
17:28:00.721 INFO  NativeLibraryLoader - Loading libgkl_utils.so from jar:file:/nix/store/cy9ckxqwrkifx7wf02hm4ww1p6lnbxg9-gatk-4.2.4.1/bin/gatk-package-4.2.4.1-local.jar!/com/intel/gkl/native/libgkl_utils.so
17:28:00.733 WARN  NativeLibraryLoader - Unable to load libgkl_utils.so from native/libgkl_utils.so (/Work/Users/apraga/bisonex/out/NA12878_NIST7035/preprocessing/applybqsr/libgkl_utils821485189051585397.so: libgomp.so.1: cannot open shared object file: No such file or directory)
17:28:00.733 WARN  IntelPairHmm - Intel GKL Utils not loaded
17:28:00.733 WARN  PairHMM - ***WARNING: Machine does not have the AVX instruction set support needed for the accelerated AVX PairHmm. Falling back to the MUCH slower LOGLESS_CACHING implementation!
17:28:00.763 INFO  ProgressMeter - Starting traversal
#+end_quote
libgomp.so est fourni par gcc donc il faut charger le module
 module load gcc@11.3.0/gcc-12.1.0
** KILL Utiliser subworkflow
CLOSED: [2023-04-02 Sun 18:08]
Notre version permet d'être plus souple
*** KILL Alignement
CLOSED: [2023-04-02 Sun 18:08] SCHEDULED: <2023-04-05 Wed>
*** KILL Vep
CLOSED: [2023-04-02 Sun 18:08] SCHEDULED: <2023-04-05 Wed>
vcf_annotate_ensemblvep
** TODO Annotation avec nextflow :annotation:
*** KILL VEP : --gene-phenotype ?
CLOSED: [2023-04-18 mar. 18:32]
Vu avec alexis : bases de données non à jour
https://www.ensembl.org/info/genome/variation/phenotype/sources_phenotype_documentation.html
*** DONE plugin VEP
CLOSED: [2023-04-18 mar. 18:32]
Cloner dépôt git avec plugin
Puis utiliser --dir_plugins
*** HOLD Utiliser code d’Alexis
*** TODO Nouvelle version avec VEP
Example avec --custom
https://www.ensembl.org/info/docs/tools/vep/script/vep_custom.html
**** DONE Ajout spliceAI
CLOSED: [2023-05-18 Thu 11:02] SCHEDULED: <2023-04-30 Sun>
plugin VEP
***** DONE Télécharger les données
CLOSED: [2023-05-11 Thu 19:01]
Difficile d'automatiser, le lien est temporaire...
***** DONE PLugin
CLOSED: [2023-05-11 Thu 20:16]
***** DONE Séparer score en plusieurs colonnes
CLOSED: [2023-05-11 Thu 20:16]
Test avec ce fichier pour avoir une ligne avec annotation et une ligne sans
#CHROM	POS	ID	REF	ALT
1	9091	.	A	C
1	69091	.	A	C
et
#+begin_src sh
rm -f postvep.tsv* && vep -i testspliceai.vcf.gz -o postvep.tsv --tab  --dir 109 --merged --pic

[3.14909]

[2.16414]

L    ALL       525466    491355     34111      1156702     57724     605307   9384  25027       0.935084          0.895313        0.523304         0.914766
INDEL   PASS       525466    491355     34111      1156702     57724     605307   9384  25027       0.935084          0.895313        0.523304         0.914766
  SNP    ALL      3365115   3358399      6716      5666020     21995    2284364   4194   1125       0.998004          0.993496        0.403169         0.995745
  SNP   PASS      3365115   3358399      6716      5666020     21995    2284364   4194   1125       0.998004          0.993496        0.403169         0.995745
 TRUTH.TOTAL.TiTv_ratio  QUERY.TOTAL.TiTv_ratio  TRUTH.TOTAL.het_hom_ratio  QUERY.TOTAL.het_hom_ratio
                    NaN                     NaN                   1.528276                   2.752637
                    NaN                     NaN                   1.528276                   2.752637
               2.100129                1.473519                   1.581196                   1.795603
               2.100129                1.473519                   1.581196                   1.795603
***** KILL Avec python2
CLOSED: [2023-02-17 Fri 19:25]
****** KILL avec nix
CLOSED: [2023-02-17 Fri 19:25]
conda create -n python2 python=2.7 anaconda
****** KILL avec conda
CLOSED: [2023-02-17 Fri 19:25]
******* Gentoo: regex_error sur test...
Ok avec bash !
#+begin_src
anaconda3/bin/conda create --name py2 python=2.7
conda activate py2
conda install -c bioconda hap.py
#+end_src
******** Faire tourner les tests.
Il faut remplace bin/test_haplotypes par test_haplotypes dans src/sh/run_tests.sh
#+begin_src sh
 HGREF=../genome/GRCh38/GCA_000001405.15_GRCh38_no_alt_analysis_set.fasta HCDIR=~/anaconda3/envs/py2/bin bash src/sh/run_tests.sh
#+end_src
Echec:
test_haplotypes: /opt/conda/conda-bld/work/hap.py-0.3.7/src/c++/lib/tools/Fasta.cpp:81: MMappedFastaFile::MMappedFastaFile(const string&): Assertion `fd != -1' failed.
unknown location(0): fatal error in "testVariantPrimitiveSplitter": signal: SIGABRT (application abort requested)
/opt/conda/conda-bld/work/hap.py-0.3.7/src/c++/test/test_align.cpp(298): last checkpoint
******** Chr21
HGREF=../genome/GRCh38/GCA_000001405.15_GRCh38_no_alt_analysis_set.fasta hap.py        example/happy/PG_NA12878_chr21.vcf.gz       example/happy/NA12878_chr21.vcf.gz       -f example/happy/PG_Conf_chr21.bed.gz       -o test
******* Helios
échec
** TODO T2T :T2T:
Toutes les ressourcs sont décrites ici
https://github.com/marbl/CHM13
Détails sur le pipeline
https://genome.ucsc.edu/cgi-bin/hgTrackUi?db=hub_3267197_GCA_009914755.4&c=CP068277.2&g=hub_3267197_hgLiftOver
*** DONE Alignement
CLOSED: [2023-06-26 Mon 19:42]
NXF_OPTS=-D"user.name=${USER}" nextflow run main.nf -profile standard,helios  --input="/Work/Groups/bisonex/data/giab/*_R{1,2}_001.fastq.gz" --id=NA12878-T2T -bg
SCHEDULED: <2023-06-14 Wed>
*** DONE Haplotypecaller
CLOSED: [2023-06-26 Mon 19:42] SCHEDULED: <2023-06-15 Thu>
*** TODO Filtres
SCHEDULED: <2023-07-10 Mon>
*** Liftover pipelines
:PROPERTIES:
:ID:       d2280207-3f65-4a31-a291-41fa9a9658c2
:END:
Contient les chain files
** TODO Indicateurs qualité
SCHEDULED: <2023-07-07 Fri>
*** Idée
Raredisease:
- FastQC : nombreuses statistiques. Non disponible Nix
- Mosdepth : calcule la profondeur (2x plus rapide que samtools depth). Nix
- MultiQC : fusionne juste les résultats des analyses. Non disponible nix
- Picard's CollectMutipleMetrics, CollectHsMetrics, and CollectWgsMetrics
- Qualimap : alternative fastqc ? Non disponible nix
- Sentieon's WgsMetricsAlgo : propriétaire
- TIDDIT's cov : TIDIT = remaninement chromosomique
Sarek:
- alignment statistics : samtools stats, mosdepth
- QC : MultiQC
MultiQC : non disponible Nix
** TODO vérifier si normalisation
SCHEDULED: <2023-07-08 Sat>
** TODO Rajouter vérification hgvs
SCHEDULED: <2023-07-08 Sat>
** DONE Exécution
CLOSED: [2022-09-13 Tue 21:37]
*** KILL test Bionix
*** KILL Implémenter execution avec Nix ?
Voir https://academic.oup.com/gigascience/article/9/11/giaa121/5987272?login=false
pour un exemple.
Probablement plus simple d’utiliser Nix pour gestion de l’environnement et snakemake pour l’exécution
Pas d’accès internet depuis le cluster
*** DONE nextflow
CLOSED: [2022-09-13 Tue 21:37]
**** TODO Bug scheduler SGE
Le job se fait tuer car l'utilisateur n'est pas passé correctement à nextflow
***** DONE Forcer l'utilisateur à l'exécution
CLOSED: [2023-04-01 Sat 17:57]
NXF_OPTS=-D"user.name=alex"
***** DONE Vérifier si le problème persiste avec 22.10.6
CLOSED: [2023-04-01 Sat 18:38] SCHEDULED: <2023-04-01 Sat>
oui
***** KILL Packager l'utilisateur dans le programme ?
Mauvaise idée..
** TODO Preprocessing avec nextflow
*** TODO Map to reference
**** TODO Sample ID dans header
/Work/Users/apraga/bisonex/out/63003856_S135/preprocessing/baserecalibrator
*** DONE Mark duplicate
CLOSED: [2022-10-09 Sun 22:30]
*** DONE Recalibrate base quality score
CLOSED: [2022-10-09 Sun 22:30]
** DONE Variant calling avec Nextflow
CLOSED: [2022-11-19 Sat 21:34]
*** DONE Haplotype caller
CLOSED: [2022-10-09 Sun 22:40]
*** DONE Filter variants
CLOSED: [2022-10-09 Sun 22:40]
*** DONE Filter common snp not clinvar path
CLOSED: [2022-11-07 Mon 23:00]
Voir [[*common dbSNP not clinvar patho][common dbSNP not clinvar patho]]
*** DONE Filter variant only in consensual sequence
CLOSED: [2022-11-08 Tue 22:23]
*** DONE Filter technical variants
CLOSED: [2022-11-19 Sat 21:34]
*** DONE Utilise AVX pour accélerer l'exécution
CLOSED: [2023-04-29 Sat 15:46]
Sans cela, on a l'avertissement
#+begin_quote
17:28:00.720 INFO  PairHMM - OpenMP multi-threaded AVX-accelerated native PairHMM implementation is not supported
17:28:00.721 INFO  NativeLibraryLoader - Loading libgkl_utils.so from jar:file:/nix/store/cy9ckxqwrkifx7wf02hm4ww1p6lnbxg9-gatk-4.2.4.1/bin/gatk-package-4.2.4.1-local.jar!/com/intel/gkl/native/libgkl_utils.so
17:28:00.733 WARN  NativeLibraryLoader - Unable to load libgkl_utils.so from native/libgkl_utils.so (/Work/Users/apraga/bisonex/out/NA12878_NIST7035/preprocessing/applybqsr/libgkl_utils821485189051585397.so: libgomp.so.1: cannot open shared object file: No such file or directory)
17:28:00.733 WARN  IntelPairHmm - Intel GKL Utils not loaded
17:28:00.733 WARN  PairHMM - ***WARNING: Machine does not have the AVX instruction set support needed for the accelerated AVX PairHmm. Falling back to the MUCH slower LOGLESS_CACHING implementation!
17:28:00.763 INFO  ProgressMeter - Starting traversal
#+end_quote
libgomp.so est fourni par gcc donc il faut charger le module
 module load gcc@11.3.0/gcc-12.1.0
** KILL Utiliser subworkflow
CLOSED: [2023-04-02 Sun 18:08]
Notre version permet d'être plus souple
*** KILL Alignement
CLOSED: [2023-04-02 Sun 18:08] SCHEDULED: <2023-04-05 Wed>
*** KILL Vep
CLOSED: [2023-04-02 Sun 18:08] SCHEDULED: <2023-04-05 Wed>
vcf_annotate_ensemblvep
** TODO Annotation avec nextflow :annotation:
*** KILL VEP : --gene-phenotype ?
CLOSED: [2023-04-18 mar. 18:32]
Vu avec alexis : bases de données non à jour
https://www.ensembl.org/info/genome/variation/phenotype/sources_phenotype_documentation.html
*** DONE plugin VEP
CLOSED: [2023-04-18 mar. 18:32]
Cloner dépôt git avec plugin
Puis utiliser --dir_plugins
*** HOLD Utiliser code d’Alexis
*** TODO Nouvelle version avec VEP
Example avec --custom
https://www.ensembl.org/info/docs/tools/vep/script/vep_custom.html
**** DONE Ajout spliceAI
CLOSED: [2023-05-18 Thu 11:02] SCHEDULED: <2023-04-30 Sun>
plugin VEP
***** DONE Télécharger les données
CLOSED: [2023-05-11 Thu 19:01]
Difficile d'automatiser, le lien est temporaire...
***** DONE PLugin
CLOSED: [2023-05-11 Thu 20:16]
***** DONE Séparer score en plusieurs colonnes
CLOSED: [2023-05-11 Thu 20:16]
Test avec ce fichier pour avoir une ligne avec annotation et une ligne sans
#CHROM	POS	ID	REF	ALT
1	9091	.	A	C
1	69091	.	A	C
et
#+begin_src sh
rm -f postvep.tsv* && vep -i testspliceai.vcf.gz -o postvep.tsv --tab  --dir 109 --merged --pic

Replacement in projects/bisonex.org at line 32 [4.35]

B:BD[5.23102] → [5.23102:24607]

B:BD[5.24607] → [2.17920:24607]

34 |
| HG003   | vcfeval   | indel |   0.8363 |    0.9115 |
| HG003   | vcfeval   | snp   |   0.9069 |    0.9928 |
| HG003   | happy     | INDEL | 0.838521 |  0.917296 |
| HG003   | happy     | SNP   | 0.907466 |  0.991204 |
| HG004   | happy     | INDEL | 0.856835 |  0.925086 |
| HG004   | happy     | SNP   | 0.905067 |  0.992704 |
| HG004   | vcfeval   | indel |   0.8568 |    0.9240 |
| HG004   | vcfeval   | snp   |   0.9048 |    0.9938 |
**** TODO télécharger données avec Nextflow :hg38:
***** DONE Renommer les chromosomes
CLOSED: [2023-02-17 Fri 19:30]
****** DONE Genome de reference NCBI
CLOSED: [2023-02-25 Sat 19:46]
****** DONE Bed avec les exons
CLOSED: [2023-03-29 Wed 23:04]
****** DONE hg19
CLOSED: [2023-02-26 Sun 22:37]
****** DONE hg38
CLOSED: [2023-03-29 Wed 23:04]
- [X] Télécharger hg19 : ok
- [X] convertir bed en interval list
picard BedToIntervalList -I exons_illumina.bed  -O exons_illumina.list -SD  ../../genome/GRCh19/genomeRef.dict
- [X] puis en hg38
picard LiftOverIntervalList -I exons_illumina.list  -O exons_illumina_hg38.list --CHAIN hg19ToHg38.over.chain -SD  ../../genome/GRCh38.p13/genomeRef.dict
- [X] puis en bed
***** KILL VCF de référence
CLOSED: [2023-04-16 Sun 16:32]
****** TODO NA12878 (HG001)
******* DONE Fastq HiSeq
CLOSED: [2023-02-25 Sat 19:46]
On prend le Hiseq, qui est probablement ce qu'utilise Centogène :
https://ftp-trace.ncbi.nih.gov/ReferenceSamples/giab/data/NA12878/Garvan_NA12878_HG001_HiSeq_Exome
/
On utilisé les données "trimmés" (https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1069-7), i.e qui ont enlevé les fragments plus petits que la taille d'un read.
Informations:
- https://ftp-trace.ncbi.nih.gov/ReferenceSamples/giab/data/NA12878/Garvan_NA12878_HG001_HiSeq_Exome/Garvan_NA12878_HG001_HiSeq_Exome.README
- Sequencer: HiSeq2500
- kit: Nextera Rapid Capture Exome and Expanded Exome
Il y a 2 samples (NIST7035 et NIST7086), chacun sur 2 lanes -> à concaténer
NB : liste techno illumina https://www.illumina.com/systems/sequencing-platforms.html
Hiseq postérieur nextseq 550
******* TODO Fastq hiseq sans trimming
******* DONE Capture : Exons (bed)
CLOSED: [2023-02-25 Sat 19:46]
https://ftp-trace.ncbi.nih.gov/ReferenceSamples/giab/data/NA12878/Garvan_NA12878_HG001_HiSeq_Exome/nexterarapidcapture_expandedexome_targetedregions.bed.gz
******* DONE Bed, vcf
CLOSED: [2023-02-24 Fri 23:45]
****** DONE Ashkenazy trio HG002, HG003, HGQ004
CLOSED: [2023-04-06 Thu 21:43] SCHEDULED: <2023-04-01 Sat>
****** KILL Chinese trio HG005, 6, 7
CLOSED: [2023-04-16 Sun 16:32]
***** KILL Fastq :fastq:
CLOSED: [2023-04-16 Sun 16:32]
****** DONE NA12878 (HG001)
CLOSED: [2023-02-25 Sat 19:46]
******* DONE Fastq HiSeq
CLOSED: [2023-02-25 Sat 19:46]
On prend le Hiseq, qui est probablement ce qu'utilise Centogène :
https://ftp-trace.ncbi.nih.gov/ReferenceSamples/giab/data/NA12878/Garvan_NA12878_HG001_HiSeq_Exome/
On utilisé les données "trimmés" (https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1069-7), i.e qui ont enlevé les fragments plus petits que la taille d'un read.
Informations:
- https://ftp-trace.ncbi.nih.gov/ReferenceSamples/giab/data/NA12878/Garvan_NA12878_HG001_HiSeq_Exome/Garvan_NA12878_HG001_HiSeq_Exome.README
- Sequencer: HiSeq2500
- kit: Nextera Rapid Capture Exome and Expanded Exome
Il y a 2 samples (NIST7035 et NIST7086), chacun sur 2 lanes -> à concaténer
NB : liste techno illumina https://www.illumina.com/systems/sequencing-platforms.html
Hiseq postérieur nextseq 550
******* DONE Capture : Exons (bed)
CLOSED: [2023-02-25 Sat 19:46]
https://ftp-trace.ncbi.nih.gov/ReferenceSamples/giab/data/NA12878/Garvan_NA12878_HG001_HiSeq_Exome/nexterarapidcapture_expandedexome_targetedregions.bed.gz
****** DONE Ashkenazy trio HG002, HG003, HG004
CLOSED: [2023-04-15 Sat 23:24] SCHEDULED: <2023-04-05 Wed>
******* DONE Capture
CLOSED: [2023-04-15 Sat 23:24]
https://ftp-trace.ncbi.nlm.nih.gov/giab/ftp/data/AshkenazimTrio/analysis/OsloUniversityHospital_Exome_GATK_jointVC_11242015/wex_Agilent_SureSelect_v05_b37.baits.slop50.merged.list
******* DONE Capture Agilent
CLOSED: [2023-04-15 Sat 23:24]
******* DONE Bam à partir des fastq
CLOSED: [2023-04-15 Sat 23:24]
Bam + index + checksum
https://raw.githubusercontent.com/genome-in-a-bottle/giab_data_indexes/master/AshkenazimTrio/alignment.index.AJtrio_OsloUniversityHospital_IlluminaExome_bwamem_GRCh37_11252015
****** KILL Chinese trio
CLOSED: [2023-04-16 Sun 16:32]
Whole exome pour HG005 seulement
******* KILL HG005
CLOSED: [2023-04-16 Sun 16:32]
https://raw.githubusercontent.com/genome-in-a-bottle/giab_data_indexes/master/ChineseTrio/alignment.index.Chinesetrio_HG005_OsloUniversityHospital_IlluminaExome_bwamem_GRCh37_11252015
**** DONE Télécharger FASTQ directement avec aws (via SRA)
CLOSED: [2023-06-30 Fri 22:30] SCHEDULED: <2023-06-27 Tue>
***** Remarques
Numéro d'accession : https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-022-08365-3/tables/1
Fastq disponible via SRA. Avec AWS, on peut accéder au fastq directement.
(Sinon il faut convertir SRA -> Fastq avec le toolkit : compliqué à configurer)
Exemple: https://trace.ncbi.nlm.nih.gov/Traces/?view=run_browser&acc=SRR2962669&display=data-access
Avantage:
- pas de conversion BAM -> fASTQ
- détail des capture
- capture en hg38 sur site du constructeur !!
- capture semblable pour ashkenazi
Inconvénient :
- NA12878 : discordance pour le nombre de paires de bases : NA12878 = 49G (donc 24G de fastq)
- capture non disponible en ligne (site agilent)
- format SRA (le lien pour les fastq n'est pas gratuit): utiliser HTTP ou leur toolkit (télécharge au format SRA puis convertit en fastq). Exemple: pour avoir 2 fastq 
  fastq-dump --split-files --gzip SRR2962669
***** Liste des runs :
https://www.ncbi.nlm.nih.gov/sra
Cherche avec numéro patient. On a le choix entre plusieurs séquenceurs Illumina
- NovaSeq 6000 TruSeq capture SRX11061536
- NovaSeq 6000 IDT capture SRX11061526
- NovaSeq 6000 Agilent SureSelect v7 capture SRX11061516
- HiSeq 4000 TruSeq capture SRX11061506
- HiSeq 4000 IDT capture SRX11061496
- HiSeq 4000 Agilent SureSelect v7 capture SRX11061486
Note: SRX = expérience, SRR = run
          Important:
          - ne pas compresser la sortie avec fasta-dump directement (lent++)
          - Fasterq-dump est plus rapide
          
  Note trueseq non disponible ?
  hg19 : https://www.biostars.org/p/144554/
IDT: lequel
https://www.idtdna.com/pages/products/next-generation-sequencing/workflow/xgen-ngs-hybridization-capture/pre-designed-hyb-cap-panels/exome-hyb-panel-v2
***** DONE HiSeq 4000 + agilent sureselect :sra:
CLOSED: [2023-06-28 Wed 22:06] SCHEDULED: <2023-06-28 Wed>
        - [ ] HG001 with Illumina HiSeq 4000 Agilent SureSelect v7 capture SRX11061486 SRR14724513	
        - [ ] HG002 with Illumina HiSeq 4000 Agilent SureSelect v7 capture SRX11061487 SRR14724512
        - [ ] HG003 with Illumina HiSeq 4000 Agilent SureSelect v7 capture SRX11061488 SRR14724511
        - [ ] HG004 with Illumina HiSeq 4000 Agilent SureSelect v7 capture SRX11061489 SRR14724510
          
        Other
 - HG005 with Illumina HiSeq 4000 Agilent SureSelect v7 capture SRX11061491 SRR14724508
           - HG006 with Illumina HiSeq 4000 Agilent SureSelect v7 capture SRX11061492 SRR14724507
           - HG007 with Illumina HiSeq 4000 Agilent SureSelect v7 capture SRX11061493 SRR14724506
******* DONE Capture agilent sureselect
CLOSED: [2023-06-30 Fri 22:30] SCHEDULED: <2023-06-28 Wed>
**** DONE NA12878 :na12878:hg38:
CLOSED: [2023-06-30 Fri 22:30]
***** DONE Discussion alexis : Mail
CLOSED: [2023-03-29 Wed 22:40]
Avec le patient NA12878 et comparaison avec hap.py du VCF de Genome In A Bottle ("gold" standard), on avait pour rappel
- sensibilité (=recall) 71% pour indel, 85% SNP
- précision  (= VPP) 69 et 97% respectivement
| Type  | TRUTH |    TP |   FN | QUERY |   FP |  UNK | FP.gt | FP.al |   Recall | Precision |
| INDEL |  4871 |  3461 | 1410 |  7048 | 1554 | 1987 |   193 |   346 | 0

[5.23102]

[2.24607]

34 |
| HG003   | vcfeval   | indel |   0.8363 |    0.9115 |
| HG003   | vcfeval   | snp   |   0.9069 |    0.9928 |
| HG003   | happy     | INDEL | 0.838521 |  0.917296 |
| HG003   | happy     | SNP   | 0.907466 |  0.991204 |
| HG004   | happy     | INDEL | 0.856835 |  0.925086 |
| HG004   | happy     | SNP   | 0.905067 |  0.992704 |
| HG004   | vcfeval   | indel |   0.8568 |    0.9240 |
| HG004   | vcfeval   | snp   |   0.9048 |    0.9938 |
**** TODO télécharger données avec Nextflow :hg38:
***** DONE Renommer les chromosomes
CLOSED: [2023-02-17 Fri 19:30]
****** DONE Genome de reference NCBI
CLOSED: [2023-02-25 Sat 19:46]
****** DONE Bed avec les exons
CLOSED: [2023-03-29 Wed 23:04]
****** DONE hg19
CLOSED: [2023-02-26 Sun 22:37]
****** DONE hg38
CLOSED: [2023-03-29 Wed 23:04]
- [X] Télécharger hg19 : ok
- [X] convertir bed en interval list
picard BedToIntervalList -I exons_illumina.bed  -O exons_illumina.list -SD  ../../genome/GRCh19/genomeRef.dict
- [X] puis en hg38
picard LiftOverIntervalList -I exons_illumina.list  -O exons_illumina_hg38.list --CHAIN hg19ToHg38.over.chain -SD  ../../genome/GRCh38.p13/genomeRef.dict
- [X] puis en bed
***** KILL VCF de référence
CLOSED: [2023-04-16 Sun 16:32]
****** TODO NA12878 (HG001)
******* DONE Fastq HiSeq
CLOSED: [2023-02-25 Sat 19:46]
On prend le Hiseq, qui est probablement ce qu'utilise Centogène :
https://ftp-trace.ncbi.nih.gov/ReferenceSamples/giab/data/NA12878/Garvan_NA12878_HG001_HiSeq_Exome/
On utilisé les données "trimmés" (https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1069-7), i.e qui ont enlevé les fragments plus petits que la taille d'un read.
Informations:
- https://ftp-trace.ncbi.nih.gov/ReferenceSamples/giab/data/NA12878/Garvan_NA12878_HG001_HiSeq_Exome/Garvan_NA12878_HG001_HiSeq_Exome.README
- Sequencer: HiSeq2500
- kit: Nextera Rapid Capture Exome and Expanded Exome
Il y a 2 samples (NIST7035 et NIST7086), chacun sur 2 lanes -> à concaténer
NB : liste techno illumina https://www.illumina.com/systems/sequencing-platforms.html
Hiseq postérieur nextseq 550
******* TODO Fastq hiseq sans trimming
******* DONE Capture : Exons (bed)
CLOSED: [2023-02-25 Sat 19:46]
https://ftp-trace.ncbi.nih.gov/ReferenceSamples/giab/data/NA12878/Garvan_NA12878_HG001_HiSeq_Exome/nexterarapidcapture_expandedexome_targetedregions.bed.gz
******* DONE Bed, vcf
CLOSED: [2023-02-24 Fri 23:45]
****** DONE Ashkenazy trio HG002, HG003, HGQ004
CLOSED: [2023-04-06 Thu 21:43] SCHEDULED: <2023-04-01 Sat>
****** KILL Chinese trio HG005, 6, 7
CLOSED: [2023-04-16 Sun 16:32]
***** KILL Fastq :fastq:
CLOSED: [2023-04-16 Sun 16:32]
****** DONE NA12878 (HG001)
CLOSED: [2023-02-25 Sat 19:46]
******* DONE Fastq HiSeq
CLOSED: [2023-02-25 Sat 19:46]
On prend le Hiseq, qui est probablement ce qu'utilise Centogène :
https://ftp-trace.ncbi.nih.gov/ReferenceSamples/giab/data/NA12878/Garvan_NA12878_HG001_HiSeq_Exome/
On utilisé les données "trimmés" (https://bmcbioinformatics.biomedcentral.com/articles/10.1186/s12859-016-1069-7), i.e qui ont enlevé les fragments plus petits que la taille d'un read.
Informations:
- https://ftp-trace.ncbi.nih.gov/ReferenceSamples/giab/data/NA12878/Garvan_NA12878_HG001_HiSeq_Exome/Garvan_NA12878_HG001_HiSeq_Exome.README
- Sequencer: HiSeq2500
- kit: Nextera Rapid Capture Exome and Expanded Exome
Il y a 2 samples (NIST7035 et NIST7086), chacun sur 2 lanes -> à concaténer
NB : liste techno illumina https://www.illumina.com/systems/sequencing-platforms.html
Hiseq postérieur nextseq 550
******* DONE Capture : Exons (bed)
CLOSED: [2023-02-25 Sat 19:46]
https://ftp-trace.ncbi.nih.gov/ReferenceSamples/giab/data/NA12878/Garvan_NA12878_HG001_HiSeq_Exome/nexterarapidcapture_expandedexome_targetedregions.bed.gz
****** DONE Ashkenazy trio HG002, HG003, HG004
CLOSED: [2023-04-15 Sat 23:24] SCHEDULED: <2023-04-05 Wed>
******* DONE Capture
CLOSED: [2023-04-15 Sat 23:24]
https://ftp-trace.ncbi.nlm.nih.gov/giab/ftp/data/AshkenazimTrio/analysis/OsloUniversityHospital_Exome_GATK_jointVC_11242015/wex_Agilent_SureSelect_v05_b37.baits.slop50.merged.list
******* DONE Capture Agilent
CLOSED: [2023-04-15 Sat 23:24]
******* DONE Bam à partir des fastq
CLOSED: [2023-04-15 Sat 23:24]
Bam + index + checksum
https://raw.githubusercontent.com/genome-in-a-bottle/giab_data_indexes/master/AshkenazimTrio/alignment.index.AJtrio_OsloUniversityHospital_IlluminaExome_bwamem_GRCh37_11252015
****** KILL Chinese trio
CLOSED: [2023-04-16 Sun 16:32]
Whole exome pour HG005 seulement
******* KILL HG005
CLOSED: [2023-04-16 Sun 16:32]
https://raw.githubusercontent.com/genome-in-a-bottle/giab_data_indexes/master/ChineseTrio/alignment.index.Chinesetrio_HG005_OsloUniversityHospital_IlluminaExome_bwamem_GRCh37_11252015
**** DONE Télécharger FASTQ directement avec aws (via SRA)
CLOSED: [2023-06-30 Fri 22:30] SCHEDULED: <2023-06-27 Tue>
***** Remarques
Numéro d'accession : https://bmcgenomics.biomedcentral.com/articles/10.1186/s12864-022-08365-3/tables/1
Fastq disponible via SRA. Avec AWS, on peut accéder au fastq directement.
(Sinon il faut convertir SRA -> Fastq avec le toolkit : compliqué à configurer)
Exemple: https://trace.ncbi.nlm.nih.gov/Traces/?view=run_browser&acc=SRR2962669&display=data-access
Avantage:
- pas de conversion BAM -> fASTQ
- détail des capture
- capture en hg38 sur site du constructeur !!
- capture semblable pour ashkenazi
Inconvénient :
- NA12878 : discordance pour le nombre de paires de bases : NA12878 = 49G (donc 24G de fastq)
- capture non disponible en ligne (site agilent)
- format SRA (le lien pour les fastq n'est pas gratuit): utiliser HTTP ou leur toolkit (télécharge au format SRA puis convertit en fastq). Exemple: pour avoir 2 fastq 
  fastq-dump --split-files --gzip SRR2962669
***** Liste des runs :
https://www.ncbi.nlm.nih.gov/sra
Cherche avec numéro patient. On a le choix entre plusieurs séquenceurs Illumina
- NovaSeq 6000 TruSeq capture SRX11061536
- NovaSeq 6000 IDT capture SRX11061526
- NovaSeq 6000 Agilent SureSelect v7 capture SRX11061516
- HiSeq 4000 TruSeq capture SRX11061506
- HiSeq 4000 IDT capture SRX11061496
- HiSeq 4000 Agilent SureSelect v7 capture SRX11061486
Note: SRX = expérience, SRR = run
          Important:
          - ne pas compresser la sortie avec fasta-dump directement (lent++)
          - Fasterq-dump est plus rapide
          
  Note trueseq non disponible ?
  hg19 : https://www.biostars.org/p/144554/
IDT: lequel
https://www.idtdna.com/pages/products/next-generation-sequencing/workflow/xgen-ngs-hybridization-capture/pre-designed-hyb-cap-panels/exome-hyb-panel-v2
***** DONE HiSeq 4000 + agilent sureselect :sra:
CLOSED: [2023-06-28 Wed 22:06] SCHEDULED: <2023-06-28 Wed>
        - [ ] HG001 with Illumina HiSeq 4000 Agilent SureSelect v7 capture SRX11061486 SRR14724513	
        - [ ] HG002 with Illumina HiSeq 4000 Agilent SureSelect v7 capture SRX11061487 SRR14724512
        - [ ] HG003 with Illumina HiSeq 4000 Agilent SureSelect v7 capture SRX11061488 SRR14724511
        - [ ] HG004 with Illumina HiSeq 4000 Agilent SureSelect v7 capture SRX11061489 SRR14724510
          
        Other
 - HG005 with Illumina HiSeq 4000 Agilent SureSelect v7 capture SRX11061491 SRR14724508
           - HG006 with Illumina HiSeq 4000 Agilent SureSelect v7 capture SRX11061492 SRR14724507
           - HG007 with Illumina HiSeq 4000 Agilent SureSelect v7 capture SRX11061493 SRR14724506
******* DONE Capture agilent sureselect
CLOSED: [2023-06-30 Fri 22:30] SCHEDULED: <2023-06-28 Wed>
**** TODO Lift T2T :T2T:
#+begin_quote
We performed liftover using the GATK release 4.1.9 LiftoverVcf (Picard Version 2.23.3) tool with the default parameters. This successfully lifts over variants that map exactly from GRCh38 to T2T-CHM13v2.0 but does not recover variants with swapped reference and alternative alleles. To recover variants with swapped reference/alternative alleles, we ran LiftoverVCF again, with the RECOVER_SWAPPED_REF_ALT flag. Notably, this feature does not recover multiallelic variants, so to recover these variants, we first separated them into multiple biallelic variants, performed liftover using the RECOVER_SWAPPED_REF_ALT tag, and converted them back to their multiallelic representations.
#+end_quote
***** KILL Liftovervcf avec valeur par défaut
CLOSED: [2023-07-02 Sun 23:09] SCHEDULED: <2023-06-30 Fri>
HG002 : il manque la moitié des valeurs
hg001
[apraga@mesointeractive b946d0e6bc8d0f220eb1ad1649c20d]$ less HG004_GRCh38_1_22_v4.2.1_benchmark.vcf.lifted.vcf.gz
[apraga@mesointeractive b946d0e6bc8d0f220eb1ad1649c20d]$ zgrep -c '^chr' HG004_GRCh38_1_22_v4.2.1_benchmark.vcf.lifted.vcf.gz
2168972
[apraga@mesointeractive b946d0e6bc8d0f220eb1ad1649c20d]$ zgrep -c '^chr' HG004_GRCh38_1_22_v4.2.1_benchmark.vcf.unlifted.vcf.gz
1862374
[apraga@mesointeractive b946d0e6bc8d0f220eb1ad1649c20d]$ zgrep -c '^chr' HG004_GRCh38_1_22_v4.2.1_benchmark.vcf.gz
4031346
***** DONE liftover bed
CLOSED: [2023-07-02 Sun 23:09] SCHEDULED: <2023-06-30 Fri>
792 of 217488 intervals failed (0.364158%) to liftover, encompassing 219109 of 35718732 bases (0.613429%).
 wc -l capture/Agilent_SureSelect_All_Exons_v7_hg38_Regions.bed
217488 capture/Agilent_SureSelect_All_Exons_v7_hg38_Regions.bed
wc -l work/e4/9981dc539a2373c2beeaa0affc3497/Agilent_SureSelect_All_Exons_v7_hg38_Regions_hg38.interval_list
On a donc perdu 1000 zones
***** DONE Liftovervcf avec variant échangé référence/alternative ?
CLOSED: [2023-07-02 Sun 23:09]
***** TODO Comprendre pourquoi HG001 ne passe plus
SCHEDULED: <2023-07-03 Mon>
****** TODO Comparer hg38 et T2T: 2x moinsr de variants, trop de FP et FN
T2T
| Type  | Filter | TRUTH.TOTAL | TRUTH.TP | TRUTH.FN | QUERY.TOTAL | QUERY.FP | QUERY.UNK | FP.gt | FP.al | METRIC.Recall | METRIC.Precision | METRIC.Frac_NA | METRIC.F1_Score | TRUTH.TOTAL.TiTv_ratio | QUERY.TOTAL.TiTv_ratio | TRUTH.TOTAL.het_hom_ratio | QUERY.TOTAL.het_hom_ratio |
| INDEL | ALL    |         413 |      246 |      167 |         751 |      289 |       215 |     2 |    93 |      0.595642 |         0.460821 |       0.286285 |        0.519629 |                    NaN |                    NaN |                  2.428571 |                  2.465116 |
| INDEL | PASS   |         413 |      246 |      167 |         751 |      289 |       215 |     2 |    93 |      0.595642 |         0.460821 |       0.286285 |        0.519629 |                    NaN |                    NaN |                  2.428571 |                  2.465116 |
| SNP   | ALL    |       11236 |    10985 |      251 |       23597 |     9771 |      2841 |    26 |    58 |      0.977661 |         0.529245 |       0.120397 |        0.686734 |                3.11461 |                2.85705 |                  3.640644 |                  2.114633 |
| SNP   | PASS   |       11236 |    10985 |      251 |       23597 |     9771 |      2841 |    26 |    58 |      0.977661 |         0.529245 |       0.120397 |        0.686734 |                3.11461 |                2.85705 |                  3.640644 |                  2.114633 |
Hg38
| Type  | Filter | TRUTH.TOTAL | TRUTH.TP | TRUTH.FN | QUERY.TOTAL | QUERY.FP | QUERY.UNK | FP.gt | FP.al | METRIC.Recall | METRIC.Precision | METRIC.Frac_NA | METRIC.F1_Score | TRUTH.TOTAL.TiTv_ratio | QUERY.TOTAL.TiTv_ratio | TRUTH.TOTAL.het_hom_ratio | QUERY.TOTAL.het_hom_ratio |
| INDEL | ALL    |         549 |      489 |       60 |         899 |       64 |       340 |     8 |    17 |      0.890710 |         0.885510 |       0.378198 |        0.888102 |                    NaN |                    NaN |                  1.860963 |                  2.247273 |
| INDEL | PASS   |         549 |      489 |       60 |         899 |       64 |       340 |     8 |    17 |      0.890710 |         0.885510 |       0.378198 |        0.888102 |                    NaN |                    NaN |                  1.860963 |                  2.247273 |
| SNP   | ALL    |       21973 |    21462 |      511 |       26285 |      563 |      4263 |    68 |    16 |      0.976744 |         0.974435 |       0.162184 |        0.975588 |                3.00711 |               2.784686 |                  1.591810 |                  1.816145 |
| SNP   | PASS   |       21973 |    21462 |      511 |       26285 |      563 |      4263 |    68 |    16 |      0.976744 |         0.974435 |       0.162184 |        0.975588 |                3.00711 |               2.784686 |                  1.591810 |                  1.816145 |
******* Résumé
T2T
| Type  | TRUTH.TOTAL | TRUTH.TP | TRUTH.FN | QUERY.TOTAL | QUERY.FP | QUERY.UNK | FP.gt | FP.al | METRIC.Recall | METRIC.Precision |
| INDEL |         413 |      246 |      167 |         751 |      289 |       215 |     2 |    93 |      0.595642 |         0.460821 |
| SNP   |       11236 |    10985 |      251 |       23597 |     9771 |      2841 |    26 |    58 |      0.977661 |         0.529245 |
Hg38
| Type  | TRUTH.TOTAL | TRUTH.TP | TRUTH.FN | QUERY.TOTAL | QUERY.FP | QUERY.UNK | FP.gt | FP.al | METRIC.Recall | METRIC.Precision |
| INDEL |         549 |      489 |       60 |         899 |       64 |       340 |     8 |    17 |      0.890710 |         0.885510 |
| SNP   |       21973 |    21462 |      511 |       26285 |      563 |      4263 |    68 |    16 |      0.976744 |         0.974435 |
****** TODO Comparer quelques FP et FN
****** DONE Interesection des bed: similaire
CLOSED: [2023-07-04 Tue 23:11]
HG38
 #+begin_src sh
 bedtools intersect -a capture/Agilent_SureSelect_All_Exons_v7_hg38_Regions.bed -b /Work/Groups/bisonex/data/giab/GRCh38/HG001_GRCh38_1_22_v4.2.1_benchmark.bed  | wc -l
 #+end_src
 204280
 T2T
 #+begin_src sh
 bedtools intersect -a /Work/Groups/bisonex/data/giab/T2T/Agilent_SureSelect_All_Exons_v7_hg38_Regions_hg38_T2T.bed -b /Work/Groups/bisonex/data/giab/T2T/HG001_GRCh38_1_22_v4.2.1_benchmark_hg38_T2T.bed  | wc -l
 #+end_src
 204021
****** DONE Vérifier la ligne de commande
CLOSED: [2023-07-04 Tue 23:38]
#+begin_src sh
hap.py \
    HG001_GRCh38_1_22_v4_lifted_merged.vcf.gz \
    HG001-SRX11061486_SRR14724513-T2T.vcf.gz \
     \
    --reference chm13v2.0.fa \
    --threads 6 \
     \
    -T Agilent_SureSelect_All_Exons_v7_hg38_Regions_hg38_T2T.bed \
    --false-positives HG001_GRCh38_1_22_v4.2.1_benchmark_hg38_T2T.bed \
     \
    -o HG001
#+end_src
**** DONE NA12878 :na12878:hg38:
CLOSED: [2023-06-30 Fri 22:30]
***** DONE Discussion alexis : Mail
CLOSED: [2023-03-29 Wed 22:40]
Avec le patient NA12878 et comparaison avec hap.py du VCF de Genome In A Bottle ("gold" standard), on avait pour rappel
- sensibilité (=recall) 71% pour indel, 85% SNP
- précision  (= VPP) 69 et 97% respectivement
| Type  | TRUTH |    TP |   FN | QUERY |   FP |  UNK | FP.gt | FP.al |   Recall | Precision |
| INDEL |  4871 |  3461 | 1410 |  7048 | 1554 | 1987 |   193 |   346 | 0

Replacement in projects/bisonex.org at line 40 [4.35]

B:BD[6.21153] → [6.21153:22752]

B:BD[6.22752] → [2.26207:32800]

                  |                        |        1.4964850615114236 |        1.8339222614840989 |
| INDEL | PASS   |        2909 |     2477 |      432 |        3229 |      207 |       519 |    52 |    50 |      0.851495 |         0.923616 |       0.160731 |        0.886091 |                        |                        |        1.4964850615114236 |        1.8339222614840989 |
| SNP   | ALL    |       38406 |    34793 |     3613 |       36935 |      275 |      1868 |    37 |    15 |      0.905926 |         0.992158 |       0.050575 |        0.947083 |     2.6247759222568168 |     2.5752854654538417 |         1.588953331534934 |        1.6192536889897844 |
| SNP   | PASS   |       38406 |    34793 |     3613 |       36935 |      275 |      1868 |    37 |    15 |      0.905926 |         0.992158 |       0.050575 |        0.947083 |     2.6247759222568168 |     2.5752854654538417 |         1.588953331534934 |        1.6192536889897844 |
***** TODO Refaire : HiSeq4000 + agilent sureselect + génome "prêt à l'emploi"
SCHEDULED: <2023-06-25 Sun>
**** TODO HG003 :hg003:hg38:
***** Notes
#+begin_src sh
NXF_OPTS=-D"user.name=${USER}" nextflow run main.nf -profile standard,helios  --input /Work/Groups/bisonex/data/giab/GRCh38/HG003_{1,2}.fq.gz -bg
#+end_src
#+begin_src  sh
NXF_OPTS=-D"user.name=${USER}" nextflow run workflows/compareVCF.nf -profile standard,helios -resume --outdir=compareHG003  --test.id=HG003 --test.query=out/HG003_1/variantCalling/haplotypecaller/HG003_1.vcf.gz  --test.compare=vcfeval,happy --test.capture=data/AgilentSureSelectv05_hg38.bed
#+en
d_src
vcfeval
Threshold  True-pos-baseline  True-pos-call  False-pos  False-neg  Precision  Sensitivity  F-measure
----------------------------------------------------------------------------------------------------
    5.000              36745          36473        486       3988     0.9869       0.9021     0.9426
     None              36748          36476        495       3985     0.9866       0.9022     0.9425
$ zcat NA12878.snp_roc.tsv.gz  | tail -n 1 | awk '{print $7 $6}'
happy
Type Filter  TRUTH.TOTAL  TRUTH.TP  TRUTH.FN  QUERY.TOTAL  QUERY.FP  QUERY.UNK  FP.gt  FP.al  METRIC.Recall  METRIC.Precision  METRIC.Frac_NA  METRIC.F1_Score  TRUTH.TOTAL.TiTv_ratio  QUERY.TOTAL.TiTv_ratio  TRUTH.TOTAL.het_hom_ratio  QUERY.TOTAL.het_hom_ratio
INDEL    ALL         2731      2290       441         3092       208        577     62     53       0.838521          0.917296        0.186611         0.876141                     NaN                     NaN                   1.505145                   1.888993
INDEL   PASS         2731      2290       441         3092       208        577     62     53       0.838521          0.917296        0.186611         0.876141                     NaN                     NaN                   1.505145                   1.888993
  SNP    ALL        37997     34481      3516        36861       306       2074     33     13       0.907466          0.991204        0.056265         0.947488                2.611269                2.565915                   1.555780                   1.621727
  SNP   PASS        37997     34481      3516        36861       306       2074     33     13       0.907466          0.991204        0.056265         0.947488                2.611269                2.5659
***** TODO Refaire : HiSeq4000 + agilent sureselect + génome "prêt à l'emploi"
SCHEDULED: <2023-06-25 Sun>
**** TODO HG004 :hg38:hg004:
#+begin_src sh
NXF_OPTS=-D"user.name=${USER}" nextflow run main.nf -profile standard,helios  --input /Work/Groups/bisonex/data/giab/GRCh38/HG004_{1,2}.fq.gz -bg
#+end_src
vcfeval
Threshold  True-pos-baseline  True-pos-call  False-pos  False-neg  Precision  Sensitivity  F-measure
----------------------------------------------------------------------------------------------------
    6.000              36938          36678        421       4040     0.9887       0.9014     0.9430
     None              36942          36682        432       4036     0.9884       0.9015     0.9429
happy
 Type Filter  TRUTH.TOTAL  TRUTH.TP  TRUTH.FN  QUERY.TOTAL  QUERY.FP  QUERY.UNK  FP.gt  FP.al  METRIC.Recall  METRIC.Precision  METRIC.Frac_NA  METRIC.F1_Score  TRUTH.TOTAL.TiTv_ratio  QUERY.TOTAL.TiTv_ratio  TRUTH.TOTAL.het_hom_ratio  QUERY.TOTAL.het_hom_ratio
INDEL    ALL         2787      2388       399         3183       195        580     53     38       0.856835          0.925086        0.182218         0.889654                     NaN                     NaN                   1.507834                   1.848649
INDEL   PASS         2787      2388       399         3183       195        580     53     38       0.856835          0.925086        0.182218         0.889654                     NaN                     NaN                   1.507834                   1.848649
  SNP    ALL        38185     34560      3625        36921       254       2107     46      7       0.905067          0.992704        0.057068         0.946862                2.589175                2.553546                   1.632595                   1.653534
  SNP   PASS        38185     34560      3625        36921       254       2107     46      7       0.905067          0.992704        0.057068         0.946862                2.589175                2.553546                   1.632595                   1.653534
***** TODO Refaire : HiSeq4000 + agilent sureselect + génome "prêt à l'emploi"
SCHEDULED: <2023-06-25 Sun>
**** TODO HG002 :hg002:T2T:
SCHEDULED: <2023-07-02 Sun>
**** TODO HG003 :hg003:T2T:
SCHEDULED: <2023-07-02 Sun>
**** TODO HG002 :hg004:T2T:
SCHEDULED: <2023-07-02 Sun>
**** TODO Résumer résultats pour Paul + article :resultats:hg38:
SCHEDULED: <2023-07-02 Sun>
Refaire résultats
**** TODO Plot : ashkenazim trio :hg38:
SCHEDULED: <2023-07-02 Sun>
/Entered on/ [2023-04-16 Sun 17:29]
Refaire résultats
*** KILL Platinum genome
CLOSED: [2023-06-14 Wed 22:37]
https://emea.illumina.com/platinumgenomes.html
*** TODO Séquencer NA12878
Discussion avec Paul : sous-traitant ne nous donnera pas les données, il faut commander l'ADN
**** DONE ADN commandé
CLOSED: [2023-06-30 Fri 22:29]
** TODO Insilico :centogene:
*** TODO tous les variants centogène
**** DONE Extraire liste des SNVs
CLOSED: [2023-04-22 Sat 17:32] SCHEDULED: <2023-04-17 Mon>
***** DONE Corriger manquant à la main
CLOSED: [2023-04-22 Sat 17:31]
La sortie est sauvegardé dans git-annex : variants_success.csv
***** DONE Automatique
CLOSED: [2023-04-22 Sat 17:31]
**** DONE Convert SNVs : transcript -> génomique
CLOSED: [2023-06-03 Sat 17:16]
***** DONE Variant_recoder
CLOSED: [2023-04-26 Wed 21:21] SCHEDULED: <2023-04-22 Sat>
****** KILL Haskell: 160 manquant : recoded-success.csv
CLOSED: [2023-04-25 Tue 18:32]
La liste des variants a été générée en Haskel   l et nettoyée à la main.
On générer une liste de variant pour variant_rec            oder et on soumet tout d'un coup.
[[file:~/recherche/bisonex/parsevariants/app/Main.hs][parsevariant]]
#+begin_src haskell
recodeVariant = do
  prepareVariantRecod   er "variant_success.csv" "renamed.csv"
  runVariantRecoder "renamed.csv" "recoded.json"
#+end_src
#+RESULTS:
: <interactive>:4:3-19: error:
:     Variable not in scope: runVariantRecoder :: String -> String -> t
: gh
Problème : 160 n'ont pas pu être lu sur 820, probablement à cause du numéro mineur de transcrit
La sortie est sauvegardé dans git-annex : variants-recoded-raw.json.
****** KILL Julia
CLOSED: [2023-04-25 Tue 18:32]
On regénère la liste de variant et on passe à Julia pour préparer l'appel en parallèle à variant recoder
[[file:~/recherche/bisonex/parsevariants/variantRecoder.jl][variantRecoder.jl]]
#+begin_src julia
setupVariantRecoder(unique(init), n)
#+end_src
Puis
#+begin_src sh
parallel -a parallel-recoder.sh --jobs 10
#+end_src
On récupère les résultats
#+begin_src julia
(fails, success) = mergeVariantRecoder(n)
CSV.write(fSuccess, success)
CSV.write(fFailures, fails)
#+end_src
Certains variants ne sont pas trouvé, donc on prépare un nouveau j

[6.21153]

[2.32800]

                  |                        |        1.4964850615114236 |        1.8339222614840989 |
| INDEL | PASS   |        2909 |     2477 |      432 |        3229 |      207 |       519 |    52 |    50 |      0.851495 |         0.923616 |       0.160731 |        0.886091 |                        |                        |        1.4964850615114236 |        1.8339222614840989 |
| SNP   | ALL    |       38406 |    34793 |     3613 |       36935 |      275 |      1868 |    37 |    15 |      0.905926 |         0.992158 |       0.050575 |        0.947083 |     2.6247759222568168 |     2.5752854654538417 |         1.588953331534934 |        1.6192536889897844 |
| SNP   | PASS   |       38406 |    34793 |     3613 |       36935 |      275 |      1868 |    37 |    15 |      0.905926 |         0.992158 |       0.050575 |        0.947083 |     2.6247759222568168 |     2.5752854654538417 |         1.588953331534934 |        1.6192536889897844 |
***** TODO Refaire : HiSeq4000 + agilent sureselect + génome "prêt à l'emploi"
SCHEDULED: <2023-07-08 Sat>
**** TODO HG003 :hg003:hg38:
***** Notes
#+begin_src sh
NXF_OPTS=-D"user.name=${USER}" nextflow run main.nf -profile standard,helios  --input /Work/Groups/bisonex/data/giab/GRCh38/HG003_{1,2}.fq.gz -bg
#+end_src
#+begin_src  sh
NXF_OPTS=-D"user.name=${USER}" nextflow run workflows/compareVCF.nf -profile standard,helios -resume --outdir=compareHG003  --test.id=HG003 --test.query=out/HG003_1/variantCalling/haplotypecaller/HG003_1.vcf.gz  --test.compare=vcfeval,happy --test.capture=data/AgilentSureSelectv05_hg38.bed
#+end_src
vcfeval
Threshold  True-pos-baseline  True-pos-call  False-pos  False-neg  Precision  Sensitivity  F-measure
----------------------------------------------------------------------------------------------------
    5.000              36745          36473        486       3988     0.9869       0.9021     0.9426
     None              36748          36476        495       3985     0.9866       0.9022     0.9425
$ zcat NA12878.snp_roc.tsv.gz  | tail -n 1 | awk '{print $7 $6}'
happy
Type Filter  TRUTH.TOTAL  TRUTH.TP  TRUTH.FN  QUERY.TOTAL  QUERY.FP  QUERY.UNK  FP.gt  FP.al  METRIC.Recall  METRIC.Precision  METRIC.Frac_NA  METRIC.F1_Score  TRUTH.TOTAL.TiTv_ratio  QUERY.TOTAL.TiTv_ratio  TRUTH.TOTAL.het_hom_ratio  QUERY.TOTAL.het_hom_ratio
INDEL    ALL         2731      2290       441         3092       208        577     62     53       0.838521          0.917296        0.186611         0.876141                     NaN                     NaN                   1.505145                   1.888993
INDEL   PASS         2731      2290       441         3092       208        577     62     53       0.838521          0.917296        0.186611         0.876141                     NaN                     NaN                   1.505145                   1.888993
  SNP    ALL        37997     34481      3516        36861       306       2074     33     13       0.907466          0.991204        0.056265         0.947488                2.611269                2.565915                   1.555780                   1.621727
  SNP   PASS        37997     34481      3516        36861       306       2074     33     13       0.907466          0.991204        0.056265         0.947488                2.611269                2.5659
***** TODO Refaire : HiSeq4000 + agilent sureselect + génome "prêt à l'emploi"
SCHEDULED: <2023-07-08 Sat>
**** TODO HG004 :hg38:hg004:
#+begin_src sh
NXF_OPTS=-D"user.name=${USER}" nextflow run main.nf -profile standard,helios  --input /Work/Groups/bisonex/data/giab/GRCh38/HG004_{1,2}.fq.gz -bg
#+end_src
vcfeval
Threshold  True-pos-baseline  True-pos-call  False-pos  False-neg  Precision  Sensitivity  F-measure
----------------------------------------------------------------------------------------------------
    6.000              36938          36678        421       4040     0.9887       0.9014     0.9430
     None              36942          36682        432       4036     0.9884       0.9015     0.9429
happy
 Type Filter  TRUTH.TOTAL  TRUTH.TP  TRUTH.FN  QUERY.TOTAL  QUERY.FP  QUERY.UNK  FP.gt  FP.al  METRIC.Recall  METRIC.Precision  METRIC.Frac_NA  METRIC.F1_Score  TRUTH.TOTAL.TiTv_ratio  QUERY.TOTAL.TiTv_ratio  TRUTH.TOTAL.het_hom_ratio  QUERY.TOTAL.het_hom_ratio
INDEL    ALL         2787      2388       399         3183       195        580     53     38       0.856835          0.925086        0.182218         0.889654                     NaN                     NaN                   1.507834                   1.848649
INDEL   PASS         2787      2388       399         3183       195        580     53     38       0.856835          0.925086        0.182218         0.889654                     NaN                     NaN                   1.507834                   1.848649
  SNP    ALL        38185     34560      3625        36921       254       2107     46      7       0.905067          0.992704        0.057068         0.946862                2.589175                2.553546                   1.632595                   1.653534
  SNP   PASS        38185     34560      3625        36921       254       2107     46      7       0.905067          0.992704        0.057068         0.946862                2.589175                2.553546                   1.632595                   1.653534
***** TODO Refaire : HiSeq4000 + agilent sureselect + génome "prêt à l'emploi"
SCHEDULED: <2023-07-08 Sat>
**** STRT HG001 :hg001:T2T:
SCHEDULED: <2023-07-03 Mon>
Avec liftover : 10x moins de variants...
Type,Filter,TRUTH.TOTAL,TRUTH.TP,TRUTH.FN,QUERY.TOTAL,QUERY.FP,QUERY.UNK,FP.gt,FP.al,METRIC.Recall,METRIC.Precision,METRIC.Frac_NA,METRIC.F1_Score,TRUTH.TOTAL.TiTv_ratio,QUERY.TOTAL.TiTv_ratio,TRUTH.TOTAL.het_hom_ratio,QUERY.TOTAL.het_hom_ratio
INDEL,ALL,413,246,167,751,289,215,2,93,0.595642,0.460821,0.286285,0.519629,,,2.4285714285714284,2.4651162790697674
INDEL,PASS,413,246,167,751,289,215,2,93,0.595642,0.460821,0.286285,0.519629,,,2.4285714285714284,2.4651162790697674
SNP,ALL,11236,10985,251,23597,9771,2841,26,58,0.977661,0.529245,0.120397,0.686734,3.1146100329549617,2.857049501715406,3.640644361833953,2.1146328578975173
SNP,PASS,11236,10985,251,23597,9771,2841,26,58,0.977661,0.529245,0.120397,0.686734,3.1146100329549617,2.857049501715406,3.640644361833953,2.1146328578975173
**** TODO HG002 :hg002:T2T:
SCHEDULED: <2023-07-07 Fri>
**** TODO HG003 :hg003:T2T:
SCHEDULED: <2023-07-07 Fri>
**** TODO HG004 :hg004:T2T:
SCHEDULED: <2023-07-07 Fri>
**** TODO Résumer résultats pour Paul + article :resultats:hg38:
SCHEDULED: <2023-07-10 Mon>
Refaire résultats
**** TODO Plot : ashkenazim trio :hg38:
SCHEDULED: <2023-07-10 Mon>
/Entered on/ [2023-04-16 Sun 17:29]
Refaire résultats
*** KILL Platinum genome
CLOSED: [2023-06-14 Wed 22:37]
https://emea.illumina.com/platinumgenomes.html
*** TODO Séquencer NA12878
Discussion avec Paul : sous-traitant ne nous donnera pas les données, il faut commander l'ADN
**** DONE ADN commandé
CLOSED: [2023-06-30 Fri 22:29]
** TODO Insilico :centogene:
*** TODO tous les variants centogène
**** DONE Extraire liste des SNVs
CLOSED: [2023-04-22 Sat 17:32] SCHEDULED: <2023-04-17 Mon>
***** DONE Corriger manquant à la main
CLOSED: [2023-04-22 Sat 17:31]
La sortie est sauvegardé dans git-annex : variants_success.csv
***** DONE Automatique
CLOSED: [2023-04-22 Sat 17:31]
**** DONE Convert SNVs : transcript -> génomique
CLOSED: [2023-06-03 Sat 17:16]
***** DONE Variant_recoder
CLOSED: [2023-04-26 Wed 21:21] SCHEDULED: <2023-04-22 Sat>
****** KILL Haskell: 160 manquant : recoded-success.csv
CLOSED: [2023-04-25 Tue 18:32]
La liste des variants a été générée en Haskel   l et nettoyée à la main.
On générer une liste de variant pour variant_rec            oder et on soumet tout d'un coup.
[[file:~/recherche/bisonex/parsevariants/app/Main.hs][parsevariant]]
#+begin_src haskell
recodeVariant = do
  prepareVariantRecod   er "variant_success.csv" "renamed.csv"
  runVariantRecoder "renamed.csv" "recoded.json"
#+end_src
#+RESULTS:
: <interactive>:4:3-19: error:
:     Variable not in scope: runVariantRecoder :: String -> String -> t
: gh
Problème : 160 n'ont pas pu être lu sur 820, probablement à cause du numéro mineur de transcrit
La sortie est sauvegardé dans git-annex : variants-recoded-raw.json.
****** KILL Julia
CLOSED: [2023-04-25 Tue 18:32]
On regénère la liste de variant et on passe à Julia pour préparer l'appel en parallèle à variant recoder
[[file:~/recherche/bisonex/parsevariants/variantRecoder.jl][variantRecoder.jl]]
#+begin_src julia
setupVariantRecoder(unique(init), n)
#+end_src
Puis
#+begin_src sh
parallel -a parallel-recoder.sh --jobs 10
#+end_src
On récupère les résultats
#+begin_src julia
(fails, success) = mergeVariantRecoder(n)
CSV.write(fSuccess, success)
CSV.write(fFailures, fails)
#+end_src
Certains variants ne sont pas trouvé, donc on prépare un nouveau j

Replacement in projects/bisonex.org at line 52 [4.35]

B:BD[3.52992] → [3.52992:54745]

B:BD[3.54745] → [2.34554:38574]

x/data/xamscissors
zgrep -A4 "A00853:477:HMLWYDSX3:2:2444:22354:28870" *.fq.gz
 #+end_src
63003856_xamscissors_1.fq.gz:@A00853:477:HMLWYDSX3:2:2444:22354:28870
63003856_xamscissors_1.fq.gz:CACCGTGTCCACCCCTCCTGCCGGCATCTCTGTGACGTTGGCCTTGATGTCCTTGAAGGACATCTTGCTGTCTCCCAGGAGTCTGTAGAGGATGCCACGGTAATCGTGGTGAACACTTCCTTTCTGTC
63003856_xamscissors_1.fq.gz:+
63003856_xamscissors_1.fq.gz:FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FFFFFFFFFF:FFFFFFFFFF::FFFFFFFFFFF:FFFFFFFFFFFFFF:FFFFFFF,FFFFFF,FFFFFFFFFFFF:FF::FF
63003856_xamscissors_2.fq.gz:@A00853:477:HMLWYDSX3:2:2444:22354:28870
63003856_xamscissors_2.fq.gz:GACAGAAAGGAAGTGTTCACCACGATTACCGTGGCATCCTCTACAGACTCCTGGGAGACAGCAAGATGTCCTTCGAGGACATCAAGGCCAACGTCACAGAGATGCCGGCAGGAGGGGTGGACACGGTG
63003856_xamscissors_2.fq.gz:+
63003856_xamscissors_2.fq.gz:FF:FFF:FF:FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FFFF:F:FF:FFFFFFFFFFFFFF:FFFFFFFFFFFFFFFF,:FFF,FFFFFF:FFFFFFFFFFFFF
******** DONE Avec BLAT: sur _fix
CLOSED: [2023-06-04 Sun 21:07]
1er =
   ACTIONS      QUERY   SCORE START   END QSIZE IDENTITY  CHROM                 STRAND  START       END   SPAN
--------------------------------------------------------------------------------------------------------------
browser details YourSeq   124     1   128   128    98.5%  chr15_ML143370v1_fix  +      172243    172370    128   What is chrom_fix?
browser details YourSeq   124     1   128   128    98.5%  chr15                 +    74342974  74343101    128
browser details YourSeq    23     1    25   128    96.0%  chr19                 -    33396097  33396121     25
Second
--------------------------------------------------------------------------------------------------------------
browser details YourSeq   126     1
   128   128    99.3%  chr15_ML143370v1_fix  -      172243    172370    128   What is chrom_fix?
browser details YourSeq   126     1   128   128    99.3%  chr15                 -    74342974  74343101    128
browser details YourSeq    23   104   128   128    96.0%  chr19                 +    33396097  33396121     25
******** DONE Bwa mem à la main GRCh38.p13 : on est dans une zone NW
CLOSED: [2023-06-04 Sun 21:51]
On met les 2 reads dans des fichiers séparés puis
#+begin_src sh
cd /Work/Users/apraga/bisonex/tests/xamscissors/align
bwa mem /Work/Groups/bisonex/data/genome/GRCh38.p13/bwa/genomeRef test1.fq test2.fq
#+end_src
A00853:477:HMLWYDSX3:2:2444:22354:28870	97	NW_021160016.1	172243	0	128M	=	172243	128	CACCGTGTCCACCCCTCCTGCCGGCATCTCTGTGACGTTGGCCTTGATGTCCTTGAAGGACATCTTGCTGTCTCCCAGGAGTCTGTAGAGGATGCCACGGTAATCGTGGTGAACACTTCCTTTCTGTC	FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FFFFFFFFFF:FFFFFFFFFF::FFFFFFFFFFF:FFFFFFFFFFFFFF:FFFFFFF,FFFFFF,FFFFFFFFFFFF:FF::FF	NM:i:2	MD:Z:22A30C7MC:Z:128M	AS:i:118	XS:i:118	XA:Z:NC_000015.10,+74342974,128M,2;
A00853:477:HMLWYDSX3:2:2444:22354:28870	145	NW_021160016.1	172243	0	128M	=	172243	-128	CACCGTGTCCACCCCTCCTGCCGGCATCTCTGTGACGTTGGCCTTGATGTCCTCGAAGGACATCTTGCTGTCTCCCAGGAGTCTGTAGAGGATGCCACGGTAATCGTGGTGAACACTTCCTTTCTGTC	FFFFFFFFFFFFF:FFFFFF,FFF:,FFFFFFFFFFFFFFFF:FFFFFFFFFFFFFF:FF:F:FFFF:FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FF:FFF:FF	NM:i:1	MD:Z:22A105	MC:Z:128M	AS:i:123	XS:i:123	XA:Z:NC_000015.10,-74342974,128M,1;
******** DONE GRCh38.p14: idem
CLOSED: [2023-06-04 Sun 21:51]
A00853:477:HMLWYDSX3:2:2444:22354:28870	97	NW_021160016.1	172243	0	128M	=	172243	128	CACCGTGTCCACCCCTCCTGCCGGCATCTCTGTGACGTTGGCCTTGATGTCCTTGAAGGACATCTTGCTGTCTCCCAGGAGTCTGTAGAGGATGCCACGGTAATCGTGGTGAACACTTCCTTTCTGTC	FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FFFFFFFFFF:FFFFFFFFFF::FFFFFFFFFFF:FFFFFFFFFFFFFF:FFFFFFF,FFFFFF,FFFFFFFFFFFF:FF::FF	NM:i:2	MD:Z:22A30C7MC:Z:128M	AS:i:118	XS:i:118	XA:Z:NC_000015.10,+74342974,128M,2;
A00853:477:HMLWYDSX3:2:2444:22354:28870	145	NW_021160016.1	172243	0	128M	=	172243	-128	CACCGTGTCCACCCCTCCTGCCGGCATCTCTGTGACGTTGGCCTTGATGTCCTCGAAGGACATCTTGCTGTCTCCCAGGAGTCTGTAGAGGATGCCACGGTAATCGTGGTGAACACTTCCTTTCTGTC	FFFFFFFFFFFFF:FFFFFF,FFF:,FFFFFFFFFFFFFFFF:FFFFFFFFFFFFFF:FF:F:FFFF:FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FF:FFF:FF	NM:i:1	MD:Z:22A105	MC:Z:128M	AS:i:123	XS:i:123	XA:Z:NC_000015.10,-74342974,128M,1;
******** DONE GRCh38 : ok
CLOSED: [2023-06-04 Sun 22:15]
 bwa mem /Work/Projects/bisonex/data/genome/GRCh38/GCA_000001405.15_GRCh38_full_analysis_set.fna test1.fq test2.fq
******* DONE Vérifier que les reads ont la même qualité sur les fichiers d'origine: oui
CLOSED: [2023-06-04 Sun 21:07]
******* DONE Supprimer les NW_ ?
CLOSED: [2023-06-10 Sat 10:40] SCHEDULED: <2023-06-04 Sun>
@A00853:477:HMLWYDSX3:3:2114:14742:8860
CAGGCCAGCCGCTCAGCCCGCTCCTTTCACCCTCTGCAGGAGAGCCTCGTGGCAGGCCAGTGGAGGGACATGATGGACTACATGCTCCAAGGGGTGGCGCAGCCGAGCATGGAAGAGGGCTCTGGACAGCTCCTGGAAGGGCACTTGCAC
+
FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF
@A00853:477:HMLWYDSX3:3:2114:14742:8860
CTTTTGCTTGTCCCCAGGACGCACCTCAGGGTGGTGAAGCAAAAAAACCACGGCCCAGGAGAGGGTGGGTGCTGTGGTCTCAGTGCCACCGATCAGGAGGTCCACTGCAGCCATGTGCAAGTGCCCTTCCAGGAGCTGTCCAGAGCCCTCT
+
FFFFFFFFFFFFFFFFFFFFFFF:FFF:FFFFFFFFFFFFF,FFFFFFFFFFFF:F:FFFF:FFFFF,,FFF:FFFFFFFFFF,FFFFFFF,FFFFFFFFFFF,FFFFFFFFF:FFFF,F:FFFFF:FFFFFFFFF:FFFF,FFFFFFFFF
******* DONE Supprimer NW_ et NT_
***** TODO Phase 2 : chr22, vaf variable :T2T:
SCHEDULED: <2023-07-04 Tue>
****** TODO Phase 3 : tous SNV, vaf variable :T2T:
SCHEDULED: <2023-07-01 Sat>
***** TODO Test Indel
**** Divers
***** DONE Vérifier nombre de reads fastq - bam
CLOSED: [2022-10-09 Sun 22:31]
*** KILL Liste varants "clinically relevent" (Clinge - CT-R d)
CLOSED: [2023-06-25 Sun 15:53] SCHEDULED: <2023-06-25 Sun>
[cite:@wilcox2021]
Vu avec alexis: pas notre cas d'usage

[3.52992]

x/data/xamscissors
zgrep -A4 "A00853:477:HMLWYDSX3:2:2444:22354:28870" *.fq.gz
 #+end_src
63003856_xamscissors_1.fq.gz:@A00853:477:HMLWYDSX3:2:2444:22354:28870
63003856_xamscissors_1.fq.gz:CACCGTGTCCACCCCTCCTGCCGGCATCTCTGTGACGTTGGCCTTGATGTCCTTGAAGGACATCTTGCTGTCTCCCAGGAGTCTGTAGAGGATGCCACGGTAATCGTGGTGAACACTTCCTTTCTGTC
63003856_xamscissors_1.fq.gz:+
63003856_xamscissors_1.fq.gz:FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FFFFFFFFFF:FFFFFFFFFF::FFFFFFFFFFF:FFFFFFFFFFFFFF:FFFFFFF,FFFFFF,FFFFFFFFFFFF:FF::FF
63003856_xamscissors_2.fq.gz:@A00853:477:HMLWYDSX3:2:2444:22354:28870
63003856_xamscissors_2.fq.gz:GACAGAAAGGAAGTGTTCACCACGATTACCGTGGCATCCTCTACAGACTCCTGGGAGACAGCAAGATGTCCTTCGAGGACATCAAGGCCAACGTCACAGAGATGCCGGCAGGAGGGGTGGACACGGTG
63003856_xamscissors_2.fq.gz:+
63003856_xamscissors_2.fq.gz:FF:FFF:FF:FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FFFF:F:FF:FFFFFFFFFFFFFF:FFFFFFFFFFFFFFFF,:FFF,FFFFFF:FFFFFFFFFFFFF
******** DONE Avec BLAT: sur _fix
CLOSED: [2023-06-04 Sun 21:07]
1er =
   ACTIONS      QUERY   SCORE START   END QSIZE IDENTITY  CHROM                 STRAND  START       END   SPAN
--------------------------------------------------------------------------------------------------------------
browser details YourSeq   124     1   128   128    98.5%  chr15_ML143370v1_fix  +      172243    172370    128   What is chrom_fix?
browser details YourSeq   124     1   128   128    98.5%  chr15                 +    74342974  74343101    128
browser details YourSeq    23     1    25   128    96.0%  chr19                 -    33396097  33396121     25
Second
--------------------------------------------------------------------------------------------------------------
browser details YourSeq   126     1   128   128    99.3%  chr15_ML143370v1_fix  -      172243    172370    128   What is chrom_fix?
browser details YourSeq   126     1   128   128    99.3%  chr15                 -    74342974  74343101    128
browser details YourSeq    23   104   128   128    96.0%  chr19                 +    33396097  33396121     25
******** DONE Bwa mem à la main GRCh38.p13 : on est dans une zone NW
CLOSED: [2023-06-04 Sun 21:51]
On met les 2 reads dans des fichiers séparés puis
#+begin_src sh
cd /Work/Users/apraga/bisonex/tests/xamscissors/align
bwa mem /Work/Groups/bisonex/data/genome/GRCh38.p13/bwa/genomeRef test1.fq test2.fq
#+end_src
A00853:477:HMLWYDSX3:2:2444:22354:28870	97	NW_021160016.1	172243	0	128M	=	172243	128	CACCGTGTCCACCCCTCCTGCCGGCATCTCTGTGACGTTGGCCTTGATGTCCTTGAAGGACATCTTGCTGTCTCCCAGGAGTCTGTAGAGGATGCCACGGTAATCGTGGTGAACACTTCCTTTCTGTC	FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FFFFFFFFFF:FFFFFFFFFF::FFFFFFFFFFF:FFFFFFFFFFFFFF:FFFFFFF,FFFFFF,FFFFFFFFFFFF:FF::FF	NM:i:2	MD:Z:22A30C7MC:Z:128M	AS:i:118	XS:i:118	XA:Z:NC_000015.10,+74342974,128M,2;
A00853:477:HMLWYDSX3:2:2444:22354:28870	145	NW_021160016.1	172243	0	128M	=	172243	-128	CACCGTGTCCACCCCTCCTGCCGGCATCTCTGTGACGTTGGCCTTGATGTCCTCGAAGGACATCTTGCTGTCTCCCAGGAGTCTGTAGAGGATGCCACGGTAATCGTGGTGAACACTTCCTTTCTGTC	FFFFFFFFFFFFF:FFFFFF,FFF:,FFFFFFFFFFFFFFFF:FFFFFFFFFFFFFF:FF:F:FFFF:FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FF:FFF:FF	NM:i:1	MD:Z:22A105	MC:Z:128M	AS:i:123	XS:i:123	XA:Z:NC_000015.10,-74342974,128M,1;
******** DONE GRCh38.p14: idem
CLOSED: [2023-06-04 Sun 21:51]
A00853:477:HMLWYDSX3:2:2444:22354:28870	97	NW_021160016.1	172243	0	128M	=	172243	128	CACCGTGTCCACCCCTCCTGCCGGCATCTCTGTGACGTTGGCCTTGATGTCCTTGAAGGACATCTTGCTGTCTCCCAGGAGTCTGTAGAGGATGCCACGGTAATCGTGGTGAACACTTCCTTTCTGTC	FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FFFFFFFFFF:FFFFFFFFFF::FFFFFFFFFFF:FFFFFFFFFFFFFF:FFFFFFF,FFFFFF,FFFFFFFFFFFF:FF::FF	NM:i:2	MD:Z:22A30C7MC:Z:128M	AS:i:118	XS:i:118	XA:Z:NC_000015.10,+74342974,128M,2;
A00853:477:HMLWYDSX3:2:2444:22354:28870	145	NW_021160016.1	172243	0	128M	=	172243	-128	CACCGTGTCCACCCCTCCTGCCGGCATCTCTGTGACGTTGGCCTTGATGTCCTCGAAGGACATCTTGCTGTCTCCCAGGAGTCTGTAGAGGATGCCACGGTAATCGTGGTGAACACTTCCTTTCTGTC	FFFFFFFFFFFFF:FFFFFF,FFF:,FFFFFFFFFFFFFFFF:FFFFFFFFFFFFFF:FF:F:FFFF:FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FF:FFF:FF	NM:i:1	MD:Z:22A105	MC:Z:128M	AS:i:123	XS:i:123	XA:Z:NC_000015.10,-74342974,128M,1;
******** DONE GRCh38 : ok
CLOSED: [2023-06-04 Sun 22:15]
 bwa mem /Work/Projects/bisonex/data/genome/GRCh38/GCA_000001405.15_GRCh38_full_analysis_set.fna test1.fq test2.fq
******* DONE Vérifier que les reads ont la même qualité sur les fichiers d'origine: oui
CLOSED: [2023-06-04 Sun 21:07]
******* DONE Supprimer les NW_ ?
CLOSED: [2023-06-10 Sat 10:40] SCHEDULED: <2023-06-04 Sun>
@A00853:477:HMLWYDSX3:3:2114:14742:8860
CAGGCCAGCCGCTCAGCCCGCTCCTTTCACCCTCTGCAGGAGAGCCTCGTGGCAGGCCAGTGGAGGGACATGATGGACTACATGCTCCAAGGGGTGGCGCAGCCGAGCATGGAAGAGGGCTCTGGACAGCTCCTGGAAGGGCACTTGCAC
+
FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF:FFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFFF
@A00853:477:HMLWYDSX3:3:2114:14742:8860
CTTTTGCTTGTCCCCAGGACGCACCTCAGGGTGGTGAAGCAAAAAAACCACGGCCCAGGAGAGGGTGGGTGCTGTGGTCTCAGTGCCACCGATCAGGAGGTCCACTGCAGCCATGTGCAAGTGCCCTTCCAGGAGCTGTCCAGAGCCCTCT
+
FFFFFFFFFFFFFFFFFFFFFFF:FFF:FFFFFFFFFFFFF,FFFFFFFFFFFF:F:FFFF:FFFFF,,FFF:FFFFFFFFFF,FFFFFFF,FFFFFFFFFFF,FFFFFFFFF:FFFF,F:FFFFF:FFFFFFFFF:FFFF,FFFFFFFFF
******* DONE Supprimer NW_ et NT_
***** TODO Phase 2 : chr22, vaf variable :T2T:
SCHEDULED: <2023-07-10 Mon>
****** TODO Phase 3 : tous SNV, vaf variable :T2T:
SCHEDULED: <2023-07-07 Fri>
***** TODO Test Indel
**** Divers
***** DONE Vérifier nombre de reads fastq - bam
CLOSED: [2022-10-09 Sun 22:31]
*** KILL Liste varants "clinically relevent" (Clinge - CT-R d)
CLOSED: [2023-06-25 Sun 15:53] SCHEDULED: <2023-06-25 Sun>
[cite:@wilcox2021]
Vu avec alexis: pas notre cas d'usage