FUEJT45VG4Q5LJEVCUGSEGMTQ4DUC2JLAEIHVRSFNG6MS53NIWNAC
2MZLJLCULSL5VDEKVHPWCGZS4CW3DPOFBJKVXVFMVQ25P3VJHEUAC
C4F5CN4JMIXA76SRB5G5UDE6XHOFU3R6IKI7ONV6YWYMKVNLHQIAC
XTOXRUX7WVIRV2TMEBQDOCT2AC3Z5PBV7L7XHIRQRISOPEEBF6SAC
BJ37ADC4UGIQFL25J5OFZ4LAOJUFHIOUROKVAQNQDULZAKI53SZQC
6YUQIF5JNVCBR2ORTRWK4NQDJ6FGHUOVMUSU2MVOAXN2LE65AOTQC
BRO5ESII2PGGU4FR7DCWHYC3QK22PL6WARZPKWTRMWBSQBDIYWCAC
RHWQQAAHNHFO3FLCGVB3SIDKNOUFJGZTDNN57IQVBMXXCWX74MKAC
RNTONMNJKHIFTXWDZ4MCP7UKZYNNAZOC3ELYRVZ47TYMM5Y5NYGQC
TQO5R3F22SQNVOROF3L7XIEGLT5LXAS36MN7O5XOYGVJ5RBHTPVAC
YUIFBBZUGTZTASYNEQBB7F5P4PF3HGUPPTLSW5HIT4HEH6PT34EAC
NCBHHUESPLBDQI2VOWF74N3KMHS6MOSWQPSYBISHOTN2JQLSVLYQC
4NAHUB4Y7KKNWFRC5LPZKKHZXVLLOTPBKXZC5MK22CXJPXK4V6ZQC
7F3ARXB7ZM4WPC3FOH5RHXFHWB3MGZ6XJYJX5IH6RFQNUKOWHAOQC
HBRH3EXRMCCUNRAGVPFPMEKGY2LXCRMHAYGYW6URFK55X6HOI7NAC
G7KNVIJW7ORXWK4IX3VHPW5DIILVOT6W7U6DEDLNUZWHNDGYWKEQC
F4OH5H3ONZKUVBUI5NKYJ25B66FS22QQ7LRAO53OQX3ZBL2BL6JAC
FXA3ZBV64FML7W47IPHTAJFJHN3J3XHVHFVNYED47XFSBIGMBKRQC
D4ZJQRXSIJQJOT36KITIGKOW42ABUYVBO37CZWMCFHVJYHPP6PMAC
HK72ZI3QZZKNR4BNVO2XELQHRXTOCQMTLS7ZRDR2PON6SXGFYCOQC
DW6ZOZK6GRZ4GKRD6ZMQDR3S6AUNX5SKJFCG3Y25OUQCXELZ3CGQC
ZJOCAXXFC5X5PWLVEXXU3MX74AQ6SO4NQRP6W3PYAWBM635J3MHQC
XNMQLJSI7Y44JPOUN3F2ZARC62A5OL5YEQNAP3ZV2BU4XNCUSCRQC
QTPZ6AL5CZES5XTQHDFXSHWHU5SXXGI7EBLZMXJK7I7TGSISI4YAC
DJXPJKXTAEEBALRS3QGFLWOURDSG4AN3Y6GVIOSLP4WJD5H545RQC
2K4U2KBH2DJTK7QGVP2MMUVXJ5CXH3RZ77C4YEZCFKVNNPVYJQVAC
NC42PH7CDXO3WJ7CRGHTCKFLHDFB3BT2I6TF2LRYX77MVMPFOG2AC
U3LZ6HFXQ2PX3EIVXW4MMBMZX3RH3OI2O4SX2UD3JBBNIHH4ELYAC
MMNJGZDL5JSLFC5DKMQ4O32UJE3OQJDCZAUO6QFH42AIAWN3HKZAC
REWWIJUK7BFIO5OGMPLYNROAWADNOJURQG746IMKKDETVAGDCEEQC
IDGVMP65NAONFW3OUNEQDKXOY25QFOT7DQB6L7FMD26KEQPWWSNQC
CITWHSGYZUZTEAS2OR566P67LCIOGQ5LDNCZNNF7PV567U5QR5BAC
RWZ457JG7GN4JJKPRNLB22OHOGYSKR756OQUWLJDAEXRCHFBK42AC
4FZ6627CHEHJTPLHE7MF6ZVFJKSDUAKOBGMJZ6QBR2HARWWCXOFQC
DZ6GQN2ERJAZG3PWZC34EN32YZOAPVFNGVCMJQNMFZVK4TR57UTAC
KNZKRW5WZVVQL73LUG3GGFR5QHJJWI4LMOLHJUXUU4PHNBCBLJLAC
AWWCOU4XZXRGWAREDCX5KTC2OLMND45IZNMRYLHLVZCYZS4DUFEAC
JLH7LJC6KATCDJPI6LSA76FR7KLI4TXDMPTKOKVQ3UEJXA46EAYAC
MG6QNY2AZM3YPWL2PTIQ6NNWFFO6BRKWL3MLYJOSOAMNW6HELHEQC
FOVEJMW4FQB2D2PZVROHCZJINCCWJHPWBVDUIEIFUCASYDPJLMCQC
7U7LYQLGG64AM2OXNIL6LDKKJVZK7NQZJG3R373OKFF7AYNFJC3AC
6L4IQC5W6DQMRGOGMGAPBQ3LS3MLFVK6ELHJPWSTT6F2RWYGUD3QC
AUIPWYWYHYSI4B5NG476LIVSQQ7OU6DH5WMCD6JK5H5XAPLP72JAC
NSQVQTB5KC5XXOGI643257ZFSJHYJTBKBT5N2I32ECGFEHCA56ZQC
H32Z2LPYG775IRARE4RH2TFUR3QZG2YFDZKQOMZ3WFOA42CB56JAC
OOOQLNOD45WPP3R6XB3SVSK3HSRDVURRXC7WUNDWRJFPVZ6AWGZQC
CBJYFLVAO3MFHTQTPGAVTW6VAU3455FTUXPEF2EJ32KFQMZFGUDAC
IQHE5LMHVKZPI6VEKZY7JLQ7MWT42ERFDB5R4CIG2BSXYD3CKV5QC
65XP3JMP6I4YXA3JU2GLUAQQERECIWCJ3VWG5MCJGCOZERHVAXUQC
4NRMFG5JDCIHFLH5WFKP36ZD2XBLUHBSXJNRILIW3XSHAK23ESDAC
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 |
****** 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 Corriger FILTER : mieux mais toujours trop de négatifs. 3/4 SNP retrouvés
CLOSED: [2023-07-08 Sat 15:19] SCHEDULED: <2023-07-08 Sat>
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 98 0.595642 0.460821 0.286285 0.519629 NaN NaN 2.428571 2.465116
INDEL PASS 413 246 167 751 289 215 2 98 0.595642 0.460821 0.286285 0.519629 NaN NaN 2.428571 2.465116
SNP ALL 15883 15479 404 23597 5277 2841 46 44 0.974564 0.745760 0.120397 0.844947 3.017198 2.85705 5.560099 2.114633
SNP PASS 15883 15479 404 23597 5277 2841 46 44 0.974564 0.745760 0.120397 0.844947 3.017198 2.85705 5.560099 2.114633
******* DONE Vérifier qu'il ne reste plus de filtre autre que PASS
CLOSED: [2023-07-08 Sat 15:19]
#+begin_src
$ zgrep -c 'PASS' HG001_GRCh38_1_22_v4_lifted_merged.vcf.gz
3730505
$ zgrep -c '^chr' HG001_GRCh38_1_22_v4_lifted_merged.vcf.gz
3730506
#+end_src
****** TODO 1/4 SNP manquant ?
******* DONE Regarder avec Julia si ce sont vraiment des FP: 61/5277 qui ne le sont pas
CLOSED: [2023-07-09 Sun 12:09]
******* DONE Examiner les FP
CLOSED: [2023-07-30 Sun 22:05]
******* DONE Tester un FP
CLOSED: [2023-07-30 Sun 22:05]
2 │ chr1 608765 A G ./.:.:.:.:NOCALL:nocall:. 1/1:FP:.:ti:SNP:homalt:188
liftDown UCSC: rien en GIAB : vrai FP
3 │ chr1 762943 A G ./.:.:.:.:NOCALL:nocall:. 1/1:FP:.:ti:SNP:homalt:287
4 │ chr1 762945 A T ./.:.:.:.:NOCALL:nocall:. 1/1:FP:.:tv:SNP:homalt:287
Remaniements complexes ? Pas dans le gène en HG38
******* DONE La plupart des FP (4705/5566) sont homozygotes: erreur de référence ?
CLOSED: [2023-07-12 Wed 21:10] SCHEDULED: <2023-07-09 Sun>
Sur les 2 premiers variants, ils montrent en fait la différence entre T2T et GRCh38
Erreur à l'alignement ?
******** KILL relancer l'alignement
CLOSED: [2023-07-09 Sun 17:36]
******** DONE vérifier reads identiques hg38 et T2T: oui
CLOSED: [2023-07-09 Sun 16:36]
T2T CHR1608765
38 chr1:1180168-1180168 (
SRR14724513.24448214
SRR14724513.24448214
******* DONE Vérifier quelques variants sur IGV
CLOSED: [2023-07-09 Sun 17:36]
******* KILL Répartition des FP : cluster ?
CLOSED: [2023-07-09 Sun 17:36]
****** DONE Examiner les FP restant après correction selon séquence de référence
CLOSED: [2023-08-12 Sat 15:57]
****** HOLD Examiner les variants supprimé
****** TODO Enlever les FP qui correspondent à un changement dans le génome
******* Condition:
- pas de variation à la position en GRCh38
- variantion homozygote
- la varation en T2T correspond au changement de pair de base GRC38 -> T2T
pour les SNP:
alt_T2T[i] = DNA_GRC38[j]
avec i la position en T2T et j la position en GRCh38
Note: définir un ID n'est pas correct car les variants peuvent être modifié par happy !
******* Idée
- Pour chaque FP, c'est un "faux" FP si
- REF en hg38 == ALT en T2T
- et REF en hg38 != REF en T2T
- et variant homozygote
Comment obtenir les séquences de réferences ?
1. liftover
2. blat sur la séquence autour du variant
3. identifier quelques reads contenant le variant et regarder leur aligneement en hg38
Après discussion avec Alexis: solution 3
******* Algorithme
1. Extraire les coordonnées en T2T des faux positifs *homozygote*
2. Pour chaque faux positif
1. lister 10 reads contenant le variant
2. pour chacun de ces reads, récupérer la séquence en T2T et GRCh38 via le nom du read dans le bam
3. si la séquence en T2T modifiée par le variant est "identique" à celle en GRCh38, alors on ignore ce faux positif
Note: on ignore les reads qui ont changé de chromosome entre les version
******* DONE Résultat préliminaire
CLOSED: [2023-07-23 Sun 14:30]
cf [[file:~/roam/research/bisonex/code/giab/giab-corrected.csv][script julia]]
3498 faux positifs en moins, soit 0.89 sensibilité
julia> tp=15479
julia> fp=5277
julia> tp/(tp+fp)
0.7457602620928888
julia> tp/(tp+(fp-3498))
0.8969173716537258
On est toujours en dessous des 97%
******* HOLD Corriger proprement VCF ou résultats Happy
******* TODO Adapter pour gérer plusieurs variants par read
****** DONE Méthodologie du pangenome
CLOSED: [2023-10-03 Tue 21:28]
Voir biblio[cite:@liao2023] mais ont aligné sur GRCH38
******* DONE Mail alexis
CLOSED: [2023-10-03 Tue 21:28]
****** DONE Méthodologie T2T
CLOSED: [2023-10-16 Mon 19:42]
Mail alexis
SCHEDULED: <2023-10-04 Wed>
***** TODO Rendre simplement le nombre de vrais positifs
SCHEDULED: <2023-11-22 Wed>
***** KILL Mail Yannis
CLOSED: [2023-07-08 Sat 10:44]
***** DONE Mail GIAB pour version T2T
CLOSED: [2023-07-07 Fri 18:37]
**** TODO HG002 :hg002:T2T:
**** TODO HG003 :hg003:T2T:
**** TODO HG004 :hg004:T2T:
**** DONE Plot : ashkenazim trio :hg38:
CLOSED: [2023-07-30 Sun 16:49] SCHEDULED: <2023-07-30 Sun 15:00>
:LOGBOOK:
CLOCK: [2023-07-30 Sun 16:06]--[2023-07-30 Sun 16:35] => 0:29
CLOCK: [2023-07-30 Sun 15:39]--[2023-07-30 Sun 15:40] => 0:01
:END:
/Entered on/ [2023-04-16 Sun 17:29]
Refaire résultats
**** DONE Mail Paul sur les résultat ashkenazim +/- centogene
CLOSED: [2023-08-06 Sun 20:24] SCHEDULED: <2023-08-06 Sun>
**** DONE Relancer comparaison GIAB avec GATK 4.4.0
CLOSED: [2023-08-12 Sat 15:55]
/Entered on/ [2023-08-03 Thu 12:42]
*** TODO Platinum genome :platinum:
https://emea.illumina.com/platinumgenomes.html
**** TODO Tester sur la zone couverte par l'exome centogène
SCHEDULED: <2023-11-22 Wed>
*** DONE Séquencer NA12878 :cento:hg001:
CLOSED: [2023-10-07 Sat 17:59]
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]
**** DONE Sauvegarder les données brutes
CLOSED: [2023-07-30 Sun 14:22] SCHEDULED: <2023-07-19 Wed>
K, scality, S
**** KILL Récupérer le fichier de capture
CLOSED: [20
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 |
****** 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 Corriger FILTER : mieux mais toujours trop de négatifs. 3/4 SNP retrouvés
CLOSED: [2023-07-08 Sat 15:19] SCHEDULED: <2023-07-08 Sat>
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 98 0.595642 0.460821 0.286285 0.519629 NaN NaN 2.428571 2.465116
INDEL PASS 413 246 167 751 289 215 2 98 0.595642 0.460821 0.286285 0.519629 NaN NaN 2.428571 2.465116
SNP ALL 15883 15479 404 23597 5277 2841 46 44 0.974564 0.745760 0.120397 0.844947 3.017198 2.85705 5.560099 2.114633
SNP PASS 15883 15479 404 23597 5277 2841 46 44 0.974564 0.745760 0.120397 0.844947 3.017198 2.85705 5.560099 2.114633
******* DONE Vérifier qu'il ne reste plus de filtre autre que PASS
CLOSED: [2023-07-08 Sat 15:19]
#+begin_src
$ zgrep -c 'PASS' HG001_GRCh38_1_22_v4_lifted_merged.vcf.gz
3730505
$ zgrep -c '^chr' HG001_GRCh38_1_22_v4_lifted_merged.vcf.gz
3730506
#+end_src
****** TODO 1/4 SNP manquant ?
******* DONE Regarder avec Julia si ce sont vraiment des FP: 61/5277 qui ne le sont pas
CLOSED: [2023-07-09 Sun 12:09]
******* DONE Examiner les FP
CLOSED: [2023-07-30 Sun 22:05]
******* DONE Tester un FP
CLOSED: [2023-07-30 Sun 22:05]
2 │ chr1 608765 A G ./.:.:.:.:NOCALL:nocall:. 1/1:FP:.:ti:SNP:homalt:188
liftDown UCSC: rien en GIAB : vrai FP
3 │ chr1 762943 A G ./.:.:.:.:NOCALL:nocall:. 1/1:FP:.:ti:SNP:homalt:287
4 │ chr1 762945 A T ./.:.:.:.:NOCALL:nocall:. 1/1:FP:.:tv:SNP:homalt:287
Remaniements complexes ? Pas dans le gène en HG38
******* DONE La plupart des FP (4705/5566) sont homozygotes: erreur de référence ?
CLOSED: [2023-07-12 Wed 21:10] SCHEDULED: <2023-07-09 Sun>
Sur les 2 premiers variants, ils montrent en fait la différence entre T2T et GRCh38
Erreur à l'alignement ?
******** KILL relancer l'alignement
CLOSED: [2023-07-09 Sun 17:36]
******** DONE vérifier reads identiques hg38 et T2T: oui
CLOSED: [2023-07-09 Sun 16:36]
T2T CHR1608765
38 chr1:1180168-1180168 (
SRR14724513.24448214
SRR14724513.24448214
******* DONE Vérifier quelques variants sur IGV
CLOSED: [2023-07-09 Sun 17:36]
******* KILL Répartition des FP : cluster ?
CLOSED: [2023-07-09 Sun 17:36]
****** DONE Examiner les FP restant après correction selon séquence de référence
CLOSED: [2023-08-12 Sat 15:57]
****** HOLD Examiner les variants supprimé
****** TODO Enlever les FP qui correspondent à un changement dans le génome
******* Condition:
- pas de variation à la position en GRCh38
- variantion homozygote
- la varation en T2T correspond au changement de pair de base GRC38 -> T2T
pour les SNP:
alt_T2T[i] = DNA_GRC38[j]
avec i la position en T2T et j la position en GRCh38
Note: définir un ID n'est pas correct car les variants peuvent être modifié par happy !
******* Idée
- Pour chaque FP, c'est un "faux" FP si
- REF en hg38 == ALT en T2T
- et REF en hg38 != REF en T2T
- et variant homozygote
Comment obtenir les séquences de réferences ?
1. liftover
2. blat sur la séquence autour du variant
3. identifier quelques reads contenant le variant et regarder leur aligneement en hg38
Après discussion avec Alexis: solution 3
******* Algorithme
1. Extraire les coordonnées en T2T des faux positifs *homozygote*
2. Pour chaque faux positif
1. lister 10 reads contenant le variant
2. pour chacun de ces reads, récupérer la séquence en T2T et GRCh38 via le nom du read dans le bam
3. si la séquence en T2T modifiée par le variant est "identique" à celle en GRCh38, alors on ignore ce faux positif
Note: on ignore les reads qui ont changé de chromosome entre les version
******* DONE Résultat préliminaire
CLOSED: [2023-07-23 Sun 14:30]
cf [[file:~/roam/research/bisonex/code/giab/giab-corrected.csv][script julia]]
3498 faux positifs en moins, soit 0.89 sensibilité
julia> tp=15479
julia> fp=5277
julia> tp/(tp+fp)
0.7457602620928888
julia> tp/(tp+(fp-3498))
0.8969173716537258
On est toujours en dessous des 97%
******* HOLD Corriger proprement VCF ou résultats Happy
******* TODO Adapter pour gérer plusieurs variants par read
****** DONE Méthodologie du pangenome
CLOSED: [2023-10-03 Tue 21:28]
Voir biblio[cite:@liao2023] mais ont aligné sur GRCH38
******* DONE Mail alexis
CLOSED: [2023-10-03 Tue 21:28]
****** DONE Méthodologie T2T
CLOSED: [2023-10-16 Mon 19:42]
Mail alexis
SCHEDULED: <2023-10-04 Wed>
***** TODO Rendre simplement le nombre de vrais positifs
SCHEDULED: <2023-11-25 Sat>
***** KILL Mail Yannis
CLOSED: [2023-07-08 Sat 10:44]
***** DONE Mail GIAB pour version T2T
CLOSED: [2023-07-07 Fri 18:37]
**** TODO HG002 :hg002:T2T:
**** TODO HG003 :hg003:T2T:
**** TODO HG004 :hg004:T2T:
**** DONE Plot : ashkenazim trio :hg38:
CLOSED: [2023-07-30 Sun 16:49] SCHEDULED: <2023-07-30 Sun 15:00>
:LOGBOOK:
CLOCK: [2023-07-30 Sun 16:06]--[2023-07-30 Sun 16:35] => 0:29
CLOCK: [2023-07-30 Sun 15:39]--[2023-07-30 Sun 15:40] => 0:01
:END:
/Entered on/ [2023-04-16 Sun 17:29]
Refaire résultats
**** DONE Mail Paul sur les résultat ashkenazim +/- centogene
CLOSED: [2023-08-06 Sun 20:24] SCHEDULED: <2023-08-06 Sun>
**** DONE Relancer comparaison GIAB avec GATK 4.4.0
CLOSED: [2023-08-12 Sat 15:55]
/Entered on/ [2023-08-03 Thu 12:42]
*** TODO Platinum genome :platinum:
https://emea.illumina.com/platinumgenomes.html
**** TODO Tester sur la zone couverte par l'exome centogène
SCHEDULED: <2023-11-25 Sat>
*** DONE Séquencer NA12878 :cento:hg001:
CLOSED: [2023-10-07 Sat 17:59]
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]
**** DONE Sauvegarder les données brutes
CLOSED: [2023-07-30 Sun 14:22] SCHEDULED: <2023-07-19 Wed>
K, scality, S
**** KILL Récupérer le fichier de capture
CLOSED: [20
:
VEP chooses one block of annotation per variant, using an ordered set of criteria. This order may be customised using --pick_order.
MANE Select transcript status
MANE Plus Clinical transcript status
canonical status of transcript
APPRIS isoform annotation
transcript support level
biotype of transcript ("protein_coding" preferred)
CCDS status of transcript
consequence rank according to this table
translated, transcript or feature length (longe
r
preferred)
"Wherever possible we would discourage you from summarising data in this way. "
**** DONE Mail alexis
CLOSED: [2023-08-20 Sun 13:45] SCHEDULED: <2023-08-20 Sun>
**** TODO Données simuscop 200x
SCHEDULED: <2023-11-26 Sun>
**** DONE En T2T avec liftover (filtre = spip) : ok mais lent et trop de variants :tests:
CLOSED: [2023-09-17 Sun 17:13] SCHEDULED: <2023-09-17 Sun>
1. Conversion en bed
#+begin_src sh :dir:~/code/sanger
open snvs-cento-sanger.csv | select chrom pos | insert pos2 {$in.pos } | to csv --separator="\t" | save snvs-cento-sanger.bed -f
#+end_src
2. Liftover avec UCSC (en ligne)
NB: vérifié sur le premier résultat en cherche le read contenant le variant (samtools view -r puis samtools view | grep en T2T) et avec l'aide d'IGV, on a un variant qui correspond en
chr1:10757746
3. En supposant que l'ordre des variants n'a pas changé, on ajoute simplement REF et ALT avec annotateLifted.jl
Annotation spip *très lente* : 1h13 !
Résultat:
2×3 DataFrame
Row │ variant meanQual depth
│ String Float64 Int64
─────┼──────────────────────────────────────
1 │ chr12:g.13594572 60.0 1
2 │ chr17:g.10204026 60.0 1
144 found over 146
filter depth : another 0 missed variants
filter poly : another 0 missed variants
filter vep : another 0 missed variants
Et on a trop de variants en sortie (7330 !)
**** DONE Mail Paul avec résultats filtre en T2T + nouveau schéma
CLOSED: [2023-09-17 Sun 23:15] SCHEDULED: <2023-09-17 Sun>
** TODO Medically relevant genes
SCHEDULED: <2023-11-22 Wed>
/Entered on/ [2023-10-18 Wed 22:37]
* Ré-interprétation :reanalysis:
** DONE Lancer tests sur données brutes [225/250] <(samples.csv)> <(runs.waiting)>
CLOSED: [2023-10-14 Sat 11:58] SCHEDULED: <2023-10-08 Sun>
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- [X] 220597589_63026879
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- [X] 2300009914_63060390
- [X] 2300028784_63060001
- [X] 2300036815_63063357
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- [X] 2300083434_
:
VEP chooses one block of annotation per variant, using an ordered set of criteria. This order may be customised using --pick_order.
MANE Select transcript status
MANE Plus Clinical transcript status
canonical status of transcript
APPRIS isoform annotation
transcript support level
biotype of transcript ("protein_coding" preferred)
CCDS status of transcript
consequence rank according to this table
translated, transcript or feature length (longer preferred)
"Wherever possible we would discourage you from summarising data in this way. "
**** DONE Mail alexis
CLOSED: [2023-08-20 Sun 13:45] SCHEDULED: <2023-08-20 Sun>
**** TODO Données simuscop 200x
SCHEDULED: <2023-11-26 Sun>
**** DONE En T2T avec liftover (filtre = spip) : ok mais lent et trop de variants :tests:
CLOSED: [2023-09-17 Sun 17:13] SCHEDULED: <2023-09-17 Sun>
1. Conversion en bed
#+begin_src sh :dir:~/code/sanger
open snvs-cento-sanger.csv | select chrom pos | insert pos2 {$in.pos } | to csv --separator="\t" | save snvs-cento-sanger.bed -f
#+end_src
2. Liftover avec UCSC (en ligne)
NB: vérifié sur le premier résultat en cherche le read contenant le variant (samtools view -r puis samtools view | grep en T2T) et avec l'aide d'IGV, on a un variant qui correspond en
chr1:10757746
3. En supposant que l'ordre des variants n'a pas changé, on ajoute simplement REF et ALT avec annotateLifted.jl
Annotation spip *très lente* : 1h13 !
Résultat:
2×3 DataFrame
Row │ variant meanQual depth
│ String Float64 Int64
─────┼──────────────────────────────────────
1 │ chr12:g.13594572 60.0 1
2 │ chr17:g.10204026 60.0 1
144 found over 146
filter depth : another 0 missed variants
filter poly : another 0 missed variants
filter vep : another 0 missed variants
Et on a trop de variants en sortie (7330 !)
**** DONE Mail Paul avec résultats filtre en T2T + nouveau schéma
CLOSED: [2023-09-17 Sun 23:15] SCHEDULED: <2023-09-17 Sun>
** TODO Medically relevant genes
SCHEDULED: <2023-11-25 Sat>
/Entered on/ [2023-10-18 Wed 22:37]
* Ré-interprétation :reanalysis:
** DONE Lancer tests sur données brutes [225/250] <(samples.csv)> <(runs.waiting)>
CLOSED: [2023-10-14 Sat 11:58] SCHEDULED: <2023-10-08 Sun>
- [X] 100222_63015289
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