annovar 注释

重新用annovar注释:
先转换适合的文件格式:

~/biosoft/annovar/convert2annovar.pl -format vcf4 pooling_variants_all_variants.hg19-hg38.vcf > pooling_variants_all_variants.hg19-hg38.avinput

再下载适合的数据库文件:
下载指令如下:

(base) root@1100150:~/biosoft/annovar# ./annotate_variation.pl | grep downdb
               --downdb                   download annotation database
               --webfrom          specify the source of database (ucsc or annovar or URL) (downdb operation)
            annotate_variation.pl -downdb -webfrom annovar refGene humandb/
            annotate_variation.pl -downdb -buildver mm9 refGene mousedb/
            annotate_variation.pl -downdb -buildver hg19 -webfrom annovar esp6500siv2_all humandb/

下载的数据库:

nohup ./annotate_variation.pl -downdb -buildver hg38 -webfrom annovar ensGene humandb/ &
nohup ./annotate_variation.pl -downdb -buildver hg38 -webfrom annovar esp6500siv2_all humandb/ &
nohup ./annotate_variation.pl -downdb -buildver hg38 -webfrom annovar dbnsfp35a humandb/ &
nohup ./annotate_variation.pl -downdb -buildver hg38 -webfrom annovar gnomad30_genome humandb/ &
nohup ./annotate_variation.pl -downdb -buildver hg38 -webfrom annovar regsnpintron humandb/ &
nohup ./annotate_variation.pl -downdb -buildver hg38 -webfrom annovar avsnp150 humandb/ &
nohup ./annotate_variation.pl -downdb -buildver hg38 -webfrom annovar gme humandb/ &
nohup ./annotate_variation.pl -downdb -buildver hg38 -webfrom annovar gene4denovo201907 humandb/ &
nohup ./annotate_variation.pl -downdb -buildver hg38 -webfrom annovar 1000g2015aug humandb/ &
nohup ./annotate_variation.pl -downdb -buildver hg38 -webfrom'http://www.openbioinformatics.org/annovar/download/GDI_full_10282015.txt.gz' humandb/ &
nohup ./annotate_variation.pl -downdb -buildver hg38 -webfrom'http://www.openbioinformatics.org/annovar/download/RVIS_ExAC_4KW.txt.gz' humandb/ &
nohup ./annotate_variation.pl -downdb -buildver hg38 -webfrom'http://download.openbioinformatics.org/spidex_download_form.php' humandb/ &
nohup ./annotate_variation.pl -downdb -buildver hg38 -webfrom annovar mcap humandb/ &
nohup ./annotate_variation.pl -downdb -buildver hg38 -webfrom annovar revel humandb/ &

数据库文件来源

https://annovar.openbioinformatics.org/en/latest/user-guide/download/

- For gene-based annotation

基于基因的注释

Build Table Name Explanation Date
hg18 refGene FASTA sequences for all annotated transcripts in RefSeq Gene 20190929
hg19 refGene same as above 20190929
hg38 refGene same as above 20190929
hg18 refGeneWithVer FASTA sequences for all annotated transcripts in RefSeq Gene with version number 20190929
hg19 refGeneWithVer same as above 20190929
hg38 refGeneWithVer same as above 20190929
hg18 knownGene FASTA sequences for all annotated transcripts in UCSC Known Gene 20190929
hg19 knownGene same as above 20190929
hg38 knownGene same as above 20190929
hg18 ensGene FASTA sequences for all annotated transcripts in Gencode v31 Basic collection 20190929
hg19 ensGene same as above 20190929
hg38 ensGene same as above 20190929

- For filter-based annotation

过滤数据库

Build Table Name Explanation Date
hg18 avsift whole-exome SIFT scores for non-synonymous variants (obselete and should not be uesd any more) 20120222
hg19 avsift same as above 20120222
hg18 ljb26_all whole-exome SIFT, PolyPhen2 HDIV, PolyPhen2 HVAR, LRT, MutationTaster, MutationAssessor, FATHMM, MetaSVM, MetaLR, VEST, CADD, GERP++, PhyloP and SiPhy scores from dbNSFP version 2.6 20140925
hg19 ljb26_all same as above 20140925
hg38 ljb26_all same as above 20150520
hg18 dbnsfp30a whole-exome SIFT, PolyPhen2 HDIV, PolyPhen2 HVAR, LRT, MutationTaster, MutationAssessor, FATHMM, MetaSVM, MetaLR, VEST, CADD, GERP++, DANN, fitCons, PhyloP and SiPhy scores from dbNSFP version 3.0a 20151015
hg19 dbnsfp30a same as above 20151015
hg38 dbnsfp30a same as above 20151015
hg19 dbnsfp31a_interpro protein domain for variants 20151219
hg38 dbnsfp31a_interpro same as above 20151219
hg18 dbnsfp33a whole-exome SIFT, PolyPhen2 HDIV, PolyPhen2 HVAR, LRT, MutationTaster, MutationAssessor, FATHMM, PROVEAN, MetaSVM, MetaLR, VEST, M-CAP, CADD, GERP++, DANN, fathmm-MKL, Eigen, GenoCanyon, fitCons, PhyloP and SiPhy scores from dbNSFP version 3.3a 20170221
hg19 dbnsfp33a same as above 20170221
hg38 dbnsfp33a same as above 20170221
hg18 dbnsfp35a same as above 20180921
hg19 dbnsfp35a same as above 20180921
hg38 dbnsfp35a same as above 20180921
hg18 dbnsfp35c same as above, suitable for commercial use 20181023
hg19 dbnsfp35c same as above 20181023
hg38 dbnsfp35c same as above 20181023
hg19 dbscsnv11 dbscSNV version 1.1 for splice site prediction by AdaBoost and Random Forest 20151218
hg38 dbscsnv11 same as above 20151218
hg19 intervar_20170202 InterVar: clinical interpretation of missense variants (indels not supported) 20170202
hg19 intervar_20180118 InterVar: clinical interpretation of missense variants (indels not supported) 20180325
hg38 intervar_20180118 InterVar: clinical interpretation of missense variants (indels not supported) 20180325
hg18 cg46 alternative allele frequency in 46 unrelated human subjects sequenced by Complete Genomics 20120222
hg19 cg46 same as above index updated 2012Feb22
hg18 cg69 allele frequency in 69 human subjects sequenced by Complete Genomics 20120222
hg19 cg69 same as above 20120222
hg19 cosmic64 COSMIC database version 64 20130520
hg19 cosmic65 COSMIC database version 65 20130706
hg19 cosmic67 COSMIC database version 67 20131117
hg19 cosmic67wgs COSMIC database version 67 on WGS data 20131117
hg19 cosmic68 COSMIC database version 68 20140224
hg19 cosmic68wgs COSMIC database version 68 on WGS data 20140224
hg19 cosmic70 same as above 20140911
hg18 cosmic70 same as above 20150428
hg38 cosmic70 same as above 20150428
hg19/hg38 cosmic71, 72, ..., 80 read here
hg18 esp6500siv2_ea alternative allele frequency in European American subjects in the NHLBI-ESP project with 6500 exomes, including the indel calls and the chrY calls. This is lifted over from hg19 by myself 20141222
hg19 esp6500siv2_ea same as above 20141222
hg38 esp6500siv2_ea same as above, lifted over from hg19 by myself 20141222
hg18 esp6500siv2_aa alternative allele frequency in African American subjects in the NHLBI-ESP project with 6500 exomes, including the indel calls and the chrY calls. This is lifted over from hg19 by myself. 20141222
hg19 esp6500siv2_aa same as above 20141222
hg38 esp6500siv2_aa same as above, lifted over from hg19 by myself 20141222
hg18 esp6500siv2_all alternative allele frequency in All subjects in the NHLBI-ESP project with 6500 exomes, including the indel calls and the chrY calls. This is lifted over from hg19 by myself. 20141222
hg19 esp6500siv2_all same as above 20141222
hg38 esp6500siv2_all same as above, lifted over from hg19 by myself 20141222
hg19 exac03 ExAC 65000 exome allele frequency data for ALL, AFR (African), AMR (Admixed American), EAS (East Asian), FIN (Finnish), NFE (Non-finnish European), OTH (other), SAS (South Asian)). version 0.3. Left normalization done. 20151129
hg18 exac03 same as above 20151129
hg38 exac03 same as above 20151129
hg19 exac03nontcga ExAC on non-TCGA samples (updated header) 20160423
hg38 exac03nontcga same as above 20160423
hg19 exac03nonpsych ExAC on non-Psychiatric disease samples (updated header) 20160423
hg38 exac03nonpsych same as above 20160423
hg38 exac10 No difference as exac03 based on this; use exac03 instead X
hg19 gene4denovo201907 gene4denovo database 20191101
hg38 gene4denovo201907 gene4denovo database 20191101
hg19 gnomad_exome gnomAD exome collection (v2.0.1) 20170311
hg38 gnomad_exome gnomAD exome collection (v2.0.1) 20170311
hg19 gnomad_genome gnomAD genome collection (v2.0.1) 20170311
hg38 gnomad_genome gnomAD genome collection (v2.0.1) 20170311
hg19 gnomad211_exome gnomAD exome collection (v2.1.1), with "AF AF_popmax AF_male AF_female AF_raw AF_afr AF_sas AF_amr AF_eas AF_nfe AF_fin AF_asj AF_oth non_topmed_AF_popmax non_neuro_AF_popmax non_cancer_AF_popmax controls_AF_popmax" header 20190318
hg19 gnomad211_genome same as above 20190323
hg38 gnomad211_exome same as above 20190409
hg38 gnomad211_genome same as above 20190409
hg38 gnomad30_genome version 3.0 whole-genome data 20191104
hg19 kaviar_20150923 170 million Known VARiants from 13K genomes and 64K exomes in 34 projects 20151203
hg38 kaviar_20150923 same as above 20151203
hg19 hrcr1 40 million variants from 32K samples in haplotype reference consortium 20151203
hg38 hrcr1 same as above 20151203
hg19 abraom 2.3 million Brazilian genomic variants 20181204
hg38 abraom liftOver from above 20181204
hg18 1000g (3 data sets) alternative allele frequency data in 1000 Genomes Project 20120222
hg18 1000g2010 (3 data sets) same as above 20120222
hg18 1000g2010jul (3 data sets) same as above 20120222
hg18 1000g2012apr I lifted over the latest 1000 Genomes Project data to hg18, to help researchers working with hg18 coordinates 20120820
hg19 1000g2010nov same as above 20120222
hg19 1000g2011may same as above 20120222
hg19 1000g2012feb same as above 20130308
hg18 1000g2012apr (5 data sets) This is done by liftOver of the hg19 data below. It contains alternative allele frequency data in 1000 Genomes Project for ALL, AMR (admixed american), EUR (european), ASN (asian), AFR (african) populations 20130508
hg19 1000g2012apr (5 data sets) alternative allele frequency data in 1000 Genomes Project for ALL, AMR (admixed american), EUR (european), ASN (asian), AFR (african) populations 20120525
hg19 1000g2014aug (6 data sets) alternative allele frequency data in 1000 Genomes Project for autosomes (ALL, AFR (African), AMR (Admixed American), EAS (East Asian), EUR (European), SAS (South Asian)). Based on 201408 collection v4 (based on 201305 alignment) 20140915
hg19 1000g2014sep (6 data sets) alternative allele frequency data in 1000 Genomes Project for autosomes (ALL, AFR (African), AMR (Admixed American), EAS (East Asian), EUR (European), SAS (South Asian)). Based on 201409 collection v5 (based on 201305 alignment) 20140925
hg19 1000g2014oct (6 data sets) alternative allele frequency data in 1000 Genomes Project for autosomes (ALL, AFR (African), AMR (Admixed American), EAS (East Asian), EUR (European), SAS (South Asian)). Based on 201409 collection v5 (based on 201305 alignment) but including chrX and chrY data finally! 20141216
hg18 1000g2014oct (6 data sets) same as above 20150428
hg38 1000g2014oct (6 data sets) same as above 20150424
hg19 1000g2015aug (6 data sets) The 1000G team fixed a bug in chrX frequency calculation. Based on 201508 collection v5b (based on 201305 alignment) 20150824
hg38 1000g2015aug (6 data sets) same as above 20150824
hg19 gme Great Middle East allele frequency including NWA (northwest Africa), NEA (northeast Africa), AP (Arabian peninsula), Israel, SD (Syrian desert), TP (Turkish peninsula) and CA (Central Asia) 20161024
hg38 gme same as above 20161024
hg19 mcap M-CAP scores for non-synonymous variants 20161104
hg38 mcap same as above 20161104
hg19 mcap13 [M-CAP scores v1.3] 20181203
hg19 revel REVEL scores for non-synonymous variants 20161205
hg38 revel same as above 20161205
hg18 snp128 dbSNP with ANNOVAR index files 20120222
hg18 snp129 same as above 20120222
hg19 snp129 liftover from hg18_snp129.txt 20120809
hg18 snp130 same as above 20120222
hg19 snp130 same as above 20120222
hg18 snp131 same as above 20120222
hg19 snp131 same as above 20120222
hg18 snp132 same as above 20120222
hg19 snp132 same as above 20120222
hg18 snp135 I lifted over SNP135 to hg18 20120820
hg19 snp135 same as above 20120222
hg19 snp137 same as above 20130109
hg18 snp138 I lifted over SNP138 to hg18 20140910
hg19 snp138 same as above file and index updated 20140910
hg19 avsnp138 dbSNP138 with allelic splitting and left-normalization 20141223
hg19 avsnp142 dbSNP142 with allelic splitting and left-normalization 20141228
hg19 avsnp144 dbSNP144 with allelic splitting and left-normalization (careful with bugs!) 20151102
hg38 avsnp144 same as above 20151102
hg19 avsnp147 dbSNP147 with allelic splitting and left-normalization 20160606
hg38 avsnp142 dbSNP142 with allelic splitting and left-normalization 20160106
hg38 avsnp144 dbSNP144 with allelic splitting and left-normalization 20151102
hg38 avsnp147 dbSNP147 with allelic splitting and left-normalization 20160606
hg19 avsnp150 dbSNP150 with allelic splitting and left-normalization 20170929
hg38 avsnp150 dbSNP150 with allelic splitting and left-normalization 20170929
hg18 snp128NonFlagged dbSNP with ANNOVAR index files, after removing those flagged SNPs (SNPs < 1% minor allele frequency (MAF) (or unknown), mapping only once to reference assembly, flagged in dbSnp as "clinically associated") 20120524
hg18 snp129NonFlagged same as above 20120524
hg18 snp130NonFlagged same as above 20120524
hg19 snp130NonFlagged same as above 20120524
hg18 snp131NonFlagged same as above 20120524
hg19 snp131NonFlagged same as above 20120524
hg18 snp132NonFlagged same as above 20120524
hg19 snp132NonFlagged same as above 20120524
hg19 snp135NonFlagged same as above 20120524
hg19 snp137NonFlagged same as above 20130109
hg19 snp138NonFlagged same as above 20140222
hg19 nci60 NCI-60 human tumor cell line panel exome sequencing allele frequency data 20130724
hg18 nci60 same as above 20150428
hg38 nci60 same as above 20150428
hg19 icgc21 International Cancer Genome Consortium version 21 20160622
hg19 clinvar_20131105 CLINVAR database with Variant Clinical Significance (unknown, untested, non-pathogenic, probable-non-pathogenic, probable-pathogenic, pathogenic, drug-response, histocompatibility, other) and Variant disease name 20140430
hg19 clinvar_20140211 same as above 20140430
hg19 clinvar_20140303 same as above 20140430
hg19 clinvar_20140702 same as above 20140712
hg38 clinvar_20140702 same as above 20140712
hg19 clinvar_20140902 same as above 20140911
hg38 clinvar_20140902 same as above 20140911
hg19 clinvar_20140929 same as above 20141002
hg19 clinvar_20150330 same as above but with variant normalization 20150413
hg38 clinvar_20150330 same as above but with variant normalization 20150413
hg19 clinvar_20150629 same as above but with variant normalization 20150724
hg38 clinvar_20150629 same as above but with variant normalization 20150724
hg19 clinvar_20151201 Clinvar version 20151201 with separate columns (CLINSIG CLNDBN CLNACC CLNDSDB CLNDSDBID) 20160303
hg38 clinvar_20151201 same as avove 20160303
hg19 clinvar_20160302 Clinvar version 20160302 with separate columns (CLINSIG CLNDBN CLNACC CLNDSDB CLNDSDBID) 20171003
hg38 clinvar_20160302 same as above (updated 20171003 to handle multi-allelic variants) 20171003
hg19 clinvar_20161128 Clinvar version 20161128 with separate columns (CLINSIG CLNDBN CLNACC CLNDSDB CLNDSDBID) 20171003
hg38 clinvar_20161128 same as above (updated 20170215 to add missing header line; 20171003 to handle multi-allelic variants) 20171003
hg19 clinvar_20170130 Clinvar version 20170130 with separate columns (CLINSIG CLNDBN CLNACC CLNDSDB CLNDSDBID) 20171003
hg38 clinvar_20170130 same as above 20171003
hg19 clinvar_20170501 Clinvar version 20170130 with separate columns (CLINSIG CLNDBN CLNACC CLNDSDB CLNDSDBID) 20171003
hg38 clinvar_20170501 same as above 20171003
hg19 clinvar_20170905 Clinvar version 20170905 with separate columns (CLINSIG CLNDBN CLNACC CLNDSDB CLNDSDBID) 20171003
hg38 clinvar_20170905 same as above 20171003
hg19 clinvar_20180603 Clinvar version 20180603 with separate columns (CLNALLELEID CLNDN CLNDISDB CLNREVSTAT CLNSIG) 20180708
hg38 clinvar_20180603 same as above 20180708
hg19 clinvar_20190305 Clinvar version 20190305 with separate columns (CLNALLELEID CLNDN CLNDISDB CLNREVSTAT CLNSIG) 20190311
hg38 clinvar_20190305 same as above 20190316
hg19 clinvar_20200316 Clinvar version 20200316 with separate columns (CLNALLELEID CLNDN CLNDISDB CLNREVSTAT CLNSIG) 20200401
hg38 clinvar_20200316 same as above 20200401
hg19 popfreq_max_20150413 A database containing the maximum allele frequency from 1000G, ESP6500, ExAC and CG46 20150413
hg19 popfreq_all_20150413 A database containing all allele frequency from 1000G, ESP6500, ExAC and CG46 20150413
hg19 mitimpact2 pathogenicity predictions of human mitochondrial missense variants (see here 20150520
hg19 mitimpact24 same as above with version 2.4 20160123
hg19 regsnpintron prioritize the disease-causing probability of intronic SNVs 20180920
hg38 regsnpintron lifeOver of above 20180922
hg18 gerp++elem conserved genomic regions by GERP++ 20140223
hg19 gerp++elem same as above 20140223
mm9 gerp++elem same as above 20140223
hg18 gerp++gt2 whole-genome GERP++ scores greater than 2 (RS score threshold of 2 provides high sensitivity while still strongly enriching for truly constrained sites. ) 20120621
hg19 gerp++gt2 same as above 20120621
hg19 caddgt20 with score>20 20160607
hg19 caddgt10 CADD with score>10 20160607
hg19 cadd CADD 20140223
hg19 cadd13 CADD version 1.3 20170123
hg19 cadd13gt10 CADD version 1.3 score>10 20170123
hg19 cadd13gt20 CADD version 1.3 score>20 20170123
hg19 caddindel removed 20150505
hg19 fathmm whole-genome FATHMM_coding and FATHMM_noncoding scores (noncoding and coding scores in the 2015 version was reversed) 20160315
hg19 gwava whole genome GWAVA_region_score and GWAVA_tss_score (GWAVA_unmatched_score has bug in file), see ref. 20150623
hg19 eigen whole-genome Eigen scores, see ref 20160330

User-contributed datasets

Several generous ANNOVAR users provide additional annotation datasets that may help other users. These datasets are described below:

  • MitImpact2: pathogenicity predictions of human mitochondrial missense variants. This is prepared as filter-based annotation format and users can directly download from ANNOVAR (see table above).

  • regsnpintron: regSNP-intron uses a machine learning algorithm to prioritize the disease-causing probability of intronic SNVs. The columns are "fpr (False positive rate), disease Disease category (B: benign [FPR > 0.1]; PD: Possibly Damaging [0.05 < FPR <= 0.1]; D: Damaging [FPR <= 0.05]), splicing_site Splicing site (on/off). Splicing sites are defined as -3 to +7 for donor sites, -13 to +1 for acceptor sites.". This is prepared as filter-based annotation format and users can directly download from ANNOVAR (see table above).

  • LoFtool score: gene loss-of-function score percentiles. The smaller the percentile, the most intolerant is the gene to functional variation. The file can be downloaded here. Manuscript in preparation (please contact Dr. Joao Fadista - [email protected]). The authors would like to thank the Exome Aggregation Consortium and the groups that provided exome variant data for comparison. A full list of contributing groups can be found at http://exac.broadinstitute.org/about.

  • RVIS-ESV score: RVIS score measures genetic intolerance of genes to functional mutations, as described in Petrovski et al. Original RVIS was constructed based on patterns of standing variation in 6503 samples. The authors have recently constructed scores based on the ~61,000 samples from ExAC. There is high correlation, but more resolution for many genes. The ExAC cohort implementation is what we consider RVIS (v2). It can be downloaded here.

  • GDI score: the gene damage index (GDI) is describing the accumulated mutational damage for each human gene in the general population, and shows that highly mutated/damaged genes are unlikely to be disease-causing and yet they generate a big proportion of false positive variants harbored in such genes. Therefore removing high GDI genes is a very effective way to remove confidently false positives from WES/WGS data. More details were given in this paper. The data set includes general damage prediction (low/medium/high) for different disease type (all, Mendelian, cancer, and PID) and can be downloaded from here.

  • TMC-SNPDB: SNP database from whole exome data of 62 normal samples derived from cancer patients of Indian origin, representing 114, 309 unique germline variants. Read the manuscript here. It is useful for exome sequencing studies on Indian populations and can be downloaded from here.

  • GenoNet Scores: cell-specific functional elements predicted by GenoNet organized by chromosomes in many cell types. You must use the specific link to download the files.

Third-party datasets

Several third-party researchers have provided additional annotation datasets that can be used by ANNOVAR directly. However, users need to agree to specific license terms set forth by the third parties:

  • SPIDEX: SPIDEX 1.0 - Deep Genomics : (Xiong et al, Science 2015) Machine-learning prediction on how genetic variants affect RNA splicing. This dataset can be downloaded here.

Third-party software tools

Customprodbj is a Java-based tool for customized protein database construction. It can build the database on a single or multiple VCF files on single or multiple individuals. It can be accessed at here. Command line example: java -jar customprodbj.jar -f input_variant_file_list.txt -d annovar_database/humandb/hg19_refGeneMrna.fa -r annovar_database/humandb/hg19_refGene.txt -t -o out/.

http://www.openbioinformatics.org/annovar/download/RVIS_ExAC_4KW.txt.gz

http://www.pnas.org/content/early/2015/10/14/1518646112.abstract

http://www.openbioinformatics.org/annovar/download/GDI_full_10282015.txt.gz

http://www.openbioinformatics.org/annovar/download/GenoNetScores/ByChr/index.html

http://download.openbioinformatics.org/spidex_download_form.php

Table_annovar.pl(可一次完成三种类型的注释)
使用ANNOVAR最简单的方法就是使用table_annovar.pl进行注释,它的输入文件可以是多种格式包括VCF,输出文件已Tab分隔,每一列代表着一种注释。
注释命令示例:

~/biosoft/annovar/table_annovar.pl pooling_variants_all_variants.hg19-hg38.avinput ~/biosoft/annovar/humandb/ -buildver hg38 -outchen_test -remove -protocol refGene -operation g -nastring . -csvout -polish
~/biosoft/annovar/table_annovar.pl pooling_variants_all_variants.hg19-hg38.avinput ~/biosoft/annovar/humandb/ -buildver hg38 -outmyanno -remove -protocolrefGene,knownGene,ensGene,dbnsfp35a,esp6500siv2_all,exac03,gene4denovo201907,gnomad30_genome,1000g2015aug_all,avsnp150,clinvar_20200316,regsnpintron -operation g,g,g,f,f,f,f,f,f,f,f,f -nastring . -csvout -polish
​#-buildver hg38 表示使用hg38版本
#-out myanno 表示输出文件的前缀为myanno
# -remove 表示删除注释过程中的临时文件
# -protocol 表示注释使用的数据库,用逗号隔开,且要注意顺序
# -operation 表示对应顺序的数据库的类型(g代表gene-based、r代表region-based、f代表filter-based),用逗号隔开,注意顺序
# -nastring . 表示用点号替代缺省的值
# -csvout 表示最后输出.csv文件

输出的csv文件将包含输入的5列主要信息以及各个数据库里的注释,此外,table_annoval.pl可以直接对vcf文件进行注释(不需要转换格式),注释的内容将会放在vcf文件的“INFO”那一栏。

本次注释指令及过程信息如下:

(base) root@1100150:~/new for annovar# ~/biosoft/annovar/table_annovar.pl pooling_variants_all_variants.hg19-hg38.avinput ~/biosoft/annovar/humandb/ -buildver hg38 -out myanno -remove -protocol refGene,knownGene,ensGene,dbnsfp35a,esp6500siv2_all,exac03,gene4denovo201907,gnomad30_genome,1000g2015aug_all,avsnp150,clinvar_20200316,regsnpintron -operation g,g,g,f,f,f,f,f,f,f,f,f -nastring . -csvout -polish
-----------------------------------------------------------------
NOTICE: Processing operation=g protocol=refGene
​
NOTICE: Running with system command 
NOTICE: Output files are written to myanno.refGene.variant_function, myanno.refGene.exonic_variant_function
NOTICE: Reading gene annotation from /root/biosoft/annovar/humandb/hg38_refGene.txt ... Done with 82500 transcripts (including 20366 without coding sequence annotation) for 28265 unique genes
NOTICE: Processing next batch with 13802 unique variants in 13802 input lines
NOTICE: Reading FASTA sequences from /root/biosoft/annovar/humandb/hg38_refGeneMrna.fa ... Done with 803 sequences
WARNING: A total of 591 sequences will be ignored due to lack of correct ORF annotation
​
NOTICE: Running with system command 
-----------------------------------------------------------------
NOTICE: Processing operation=g protocol=knownGene
​
NOTICE: Running with system command 
NOTICE: Output files are written to myanno.knownGene.variant_function, myanno.knownGene.exonic_variant_function
NOTICE: Reading gene annotation from /root/biosoft/annovar/humandb/hg38_knownGene.txt ... Done with 226811 transcripts (including 118121 without coding sequence annotation) for 74691 unique genes
NOTICE: Processing next batch with 13802 unique variants in 13802 input lines
NOTICE: Reading FASTA sequences from /root/biosoft/annovar/humandb/hg38_knownGeneMrna.fa ... Done with 1335 sequences
WARNING: A total of 8181 sequences will be ignored due to lack of correct ORF annotation
​
NOTICE: Running with system command 
-----------------------------------------------------------------
NOTICE: Processing operation=g protocol=ensGene
​
NOTICE: Running with system command 
NOTICE: Output files are written to myanno.ensGene.variant_function, myanno.ensGene.exonic_variant_function
NOTICE: Reading gene annotation from /root/biosoft/annovar/humandb/hg38_ensGene.txt ... Done with 89732 transcripts (including 28806 without coding sequence annotation) for 42087 unique genes
NOTICE: Processing next batch with 13802 unique variants in 13802 input lines
NOTICE: Reading FASTA sequences from /root/biosoft/annovar/humandb/hg38_ensGeneMrna.fa ... Done with 606 sequences
WARNING: A total of 214 sequences cannot be found in /root/biosoft/annovar/humandb/hg38_ensGeneMrna.fa
(example: ENST00000293894.3#16#981807 ENST00000349496.9#3#41199438 ENST00000255192.7#5#79069716)
WARNING: A total of 385 sequences will be ignored due to lack of correct ORF annotation
​
NOTICE: Running with system command 
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NOTICE: Processing operation=f protocol=dbnsfp35a
NOTICE: Finished reading 70 column headers for '-dbtype dbnsfp35a'
​
NOTICE: Running system command 
NOTICE: Output file with variants matching filtering criteria is written to myanno.hg38_dbnsfp35a_dropped, and output file with other variants is written to myanno.hg38_dbnsfp35a_filtered
NOTICE: Processing next batch with 13802 unique variants in 13802 input lines
NOTICE: Database index loaded. Total number of bins is 552168 and the number of bins to be scanned is 2918
NOTICE: Scanning filter database /root/biosoft/annovar/humandb/hg38_dbnsfp35a.txt...Done
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NOTICE: Processing operation=f protocol=esp6500siv2_all
​
NOTICE: Running system command 
NOTICE: the --dbtype esp6500siv2_all is assumed to be in generic ANNOVAR database format
NOTICE: Output file with variants matching filtering criteria is written to myanno.hg38_esp6500siv2_all_dropped, and output file with other variants is written to myanno.hg38_esp6500siv2_all_filtered
NOTICE: Processing next batch with 13802 unique variants in 13802 input lines
NOTICE: Database index loaded. Total number of bins is 683825 and the number of bins to be scanned is 3065
NOTICE: Scanning filter database /root/biosoft/annovar/humandb/hg38_esp6500siv2_all.txt...Done
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NOTICE: Processing operation=f protocol=exac03
NOTICE: Finished reading 8 column headers for '-dbtype exac03'
​
NOTICE: Running system command 
NOTICE: Output file with variants matching filtering criteria is written to myanno.hg38_exac03_dropped, and output file with other variants is written to myanno.hg38_exac03_filtered
NOTICE: Processing next batch with 13802 unique variants in 13802 input lines
NOTICE: Database index loaded. Total number of bins is 749044 and the number of bins to be scanned is 3310
NOTICE: Scanning filter database /root/biosoft/annovar/humandb/hg38_exac03.txt...Done
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NOTICE: Processing operation=f protocol=gene4denovo201907
NOTICE: Finished reading 6 column headers for '-dbtype gene4denovo201907'
​
NOTICE: Running system command 
NOTICE: the --dbtype gene4denovo201907 is assumed to be in generic ANNOVAR database format
NOTICE: Output file with variants matching filtering criteria is written to myanno.hg38_gene4denovo201907_dropped, and output file with other variants is written to myanno.hg38_gene4denovo201907_filtered
NOTICE: Processing next batch with 13802 unique variants in 13802 input lines
NOTICE: Database index loaded. Total number of bins is 501939 and the number of bins to be scanned is 848
NOTICE: Scanning filter database /root/biosoft/annovar/humandb/hg38_gene4denovo201907.txt...Done
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NOTICE: Processing operation=f protocol=gnomad30_genome
NOTICE: Finished reading 13 column headers for '-dbtype gnomad30_genome'
​
NOTICE: Running system command 
NOTICE: Output file with variants matching filtering criteria is written to myanno.hg38_gnomad30_genome_dropped, and output file with other variants is written to myanno.hg38_gnomad30_genome_filtered
NOTICE: Processing next batch with 13802 unique variants in 13802 input lines
NOTICE: Database index loaded. Total number of bins is 2860873 and the number of bins to be scanned is 3049
NOTICE: Scanning filter database /root/biosoft/annovar/humandb/hg38_gnomad30_genome.txt...Done
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NOTICE: Processing operation=f protocol=1000g2015aug_all
​
NOTICE: Running system command 
NOTICE: Output file with variants matching filtering criteria is written to myanno.hg38_ALL.sites.2015_08_dropped, and output file with other variants is written to myanno.hg38_ALL.sites.2015_08_filtered
NOTICE: Processing next batch with 13802 unique variants in 13802 input lines
NOTICE: Database index loaded. Total number of bins is 2821635 and the number of bins to be scanned is 3052
NOTICE: Scanning filter database /root/biosoft/annovar/humandb/hg38_ALL.sites.2015_08.txt...Done
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NOTICE: Processing operation=f protocol=avsnp150
​
NOTICE: Running system command 
NOTICE: Output file with variants matching filtering criteria is written to myanno.hg38_avsnp150_dropped, and output file with other variants is written to myanno.hg38_avsnp150_filtered
NOTICE: Processing next batch with 13802 unique variants in 13802 input lines
NOTICE: Database index loaded. Total number of bins is 28304406 and the number of bins to be scanned is 9229
NOTICE: Scanning filter database /root/biosoft/annovar/humandb/hg38_avsnp150.txt...Done
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NOTICE: Processing operation=f protocol=clinvar_20200316
NOTICE: Finished reading 5 column headers for '-dbtype clinvar_20200316'
​
NOTICE: Running system command 
NOTICE: the --dbtype clinvar_20200316 is assumed to be in generic ANNOVAR database format
NOTICE: Output file with variants matching filtering criteria is written to myanno.hg38_clinvar_20200316_dropped, and output file with other variants is written to myanno.hg38_clinvar_20200316_filtered
NOTICE: Processing next batch with 13802 unique variants in 13802 input lines
NOTICE: Database index loaded. Total number of bins is 72414 and the number of bins to be scanned is 1706
NOTICE: Scanning filter database /root/biosoft/annovar/humandb/hg38_clinvar_20200316.txt...Done
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NOTICE: Processing operation=f protocol=regsnpintron
NOTICE: Finished reading 3 column headers for '-dbtype regsnpintron'
​
NOTICE: Running system command 
NOTICE: the --dbtype regsnpintron is assumed to be in generic ANNOVAR database format
NOTICE: Output file with variants matching filtering criteria is written to myanno.hg38_regsnpintron_dropped, and output file with other variants is written to myanno.hg38_regsnpintron_filtered
NOTICE: Processing next batch with 13802 unique variants in 13802 input lines
NOTICE: Database index loaded. Total number of bins is 1162669 and the number of bins to be scanned is 1874
NOTICE: Scanning filter database /root/biosoft/annovar/humandb/hg38_regsnpintron.txt...Done
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NOTICE: Multianno output file is written to myanno.hg38_multianno.csv

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