{"id":924,"date":"2023-03-15T12:10:36","date_gmt":"2023-03-15T17:10:36","guid":{"rendered":"https:\/\/www.geneticalatam.org\/?page_id=924"},"modified":"2023-03-23T22:34:53","modified_gmt":"2023-03-24T03:34:53","slug":"genomic-tools-and-databases","status":"publish","type":"page","link":"https:\/\/www.geneticalatam.org\/index.php\/genomic-tools-and-databases\/","title":{"rendered":"Genomic tools and databases"},"content":{"rendered":"\n

Genome browsers<\/strong><\/p>\n\n\n\n

IGV<\/a><\/p>\n\n\n\n

Online browser<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

Annotation sources<\/strong><\/p>\n\n\n\n

UCSC annotations<\/a> <\/p>\n\n\n\n

<\/p>\n\n\n\n

Databases<\/strong><\/p>\n\n\n\n

OMIM<\/a><\/p>\n\n\n\n

ClinVar<\/a><\/p>\n\n\n\n

Varsome<\/a><\/p>\n\n\n\n

Clingen<\/a><\/p>\n\n\n\n

<\/p>\n\n\n\n

Bioinformatics tools<\/strong><\/p>\n\n\n\n

Coding areas<\/strong><\/p>\n\n\n\n

SIFT\u2002\u2002<\/strong><\/p>\n\n\n\n

Predicts whether amino acid substitutions affect protein function. Uses comparison with other related proteins and their structures to infer the effect.<\/p>\n\n\n\n

POLYPHEN2\u2002\u2002\u2002<\/strong><\/p>\n\n\n\n

Infer the impact of amino acid change based on the physical and comparative structure causing the change.<\/p>\n\n\n\n

MUT TASTER\u2002\u2002<\/strong><\/p>\n\n\n\n

Uses a Bayesian method to predict a change at the nucleotide or amino acid level. This includes evaluation of intron borders, synonymous substitutions.<\/p>\n\n\n\n

MUT ASSESSOR\u2002\u2002\u2002\u2002\u2002\u2002<\/strong><\/p>\n\n\n\n

Evaluates the impact of an amino acid change in cancer using information from conserved sites in other homologous molecules.<\/p>\n\n\n\n

FATHMM\u2002\u2002\u2002\u2002\u2002\u2002<\/strong><\/p>\n\n\n\n

Evaluates the effect of missense mutations using a Markov conservation model on conserved protein alignments, and assesses their pathogenicity weight.<\/p>\n\n\n\n

INTRONS<\/strong><\/p>\n\n\n\n

dbscSNV RF and Ada<\/strong><\/p>\n\n\n\n

Both tools evaluate intronic cleavage regions (-3 to +8 and -12 to +2) to determine the impact of nucleotide change on splicing. The Ada version uses ensemble values to calculate the probability of impact.<\/p>\n\n\n\n

CONSERVATION<\/strong><\/p>\n\n\n\n

GERP\u2002\u2002<\/strong><\/p>\n\n\n\n

Identifies conservation elements by the pressure to remain unchanged.<\/p>\n\n\n\n

Functional Whole Genome\u2002<\/p>\n\n\n\n

GenoCanyon\u2002\u2002<\/strong><\/p>\n\n\n\n

Self-learning unsupervised annotation method that infers the functional impact of each base in the genome.<\/p>\n\n\n\n

fitCons\u2002\u2002\u2002\u2002\u2002<\/strong><\/p>\n\n\n\n

Integrates functional assays to calculate a conservation value of a genomic pattern.<\/p>\n\n\n\n

Other annotation databases<\/strong><\/p>\n\n\n\n
Table Name<\/td>Explanation<\/td>Date<\/td><\/tr>\n
1000g2015aug (6 data sets)<\/td>The 1000G team fixed a bug in chrX frequency calculation. Based on 201508 collection v5b (based on 201305 alignment)<\/td>20150824<\/td><\/tr>\n
abraom<\/td>2.3 million Brazilian genomic variants<\/td>20181204<\/td><\/tr>\n
avsnp150<\/td>dbSNP150 with allelic splitting and left-normalization<\/td>20170929<\/td><\/tr>\n
cadd13<\/td>CADD version 1.3<\/td>20170123<\/td><\/tr>\n
cadd13gt10<\/td>CADD version 1.3 score>10<\/td>20170123<\/td><\/tr>\n
cadd13gt20<\/td>CADD version 1.3 score>20<\/td>20170123<\/td><\/tr>\n
cg46<\/td>alternative allele frequency in 46 unrelated human subjects sequenced by Complete Genomics<\/td>20120222<\/td><\/tr>\n
cg69<\/td>allele frequency in 69 human subjects sequenced by Complete Genomics<\/td>20120222<\/td><\/tr>\n
clinvar_20221231<\/td>Clinvar version 20221231 with separate columns (CLNALLELEID CLNDN CLNDISDB CLNREVSTAT CLNSIG)<\/td>20230105<\/td><\/tr>\n
cosmic68wgs<\/td>COSMIC database version 68 on WGS data<\/td>20140224<\/td><\/tr>\n
dbnsfp42a<\/td>reformatted to include more columns than dbnsfp41a<\/td>20210710<\/td><\/tr>\n
dbscsnv11<\/td>dbscSNV version 1.1 for splice site prediction by AdaBoost and Random Forest<\/td>20151218<\/td><\/tr>\n
eigen<\/td>whole-genome Eigen scores, see ref<\/td>20160330<\/td><\/tr>\n
ensGene<\/td>FASTA sequences for all annotated transcripts in Gencode v43 Basic collection lifted up to hg19 (last update was 2023-02-15 at UCSC)<\/td>20230315<\/td><\/tr>\n
esp6500siv2_all<\/td>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.<\/td>20141222<\/td><\/tr>\n
exac03<\/td>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.<\/td>20151129<\/td><\/tr>\n
exac03nonpsych<\/td>ExAC on non-Psychiatric disease samples (updated header)<\/td>20160423<\/td><\/tr>\n
exac03nontcga<\/td>ExAC on non-TCGA samples (updated header)<\/td>20160423<\/td><\/tr>\n
fathmm<\/td>whole-genome FATHMM_coding and FATHMM_noncoding scores (noncoding and coding scores in the 2015 version was reversed)<\/td>20160315<\/td><\/tr>\n
gene4denovo201907<\/td>gene4denovo database<\/td>20191101<\/td><\/tr>\n
gene4denovo201907<\/td>gene4denovo database<\/td>20191101<\/td><\/tr>\n
gerp++elem<\/td>conserved genomic regions by GERP++<\/td>20140223<\/td><\/tr>\n
gerp++gt2<\/td>whole-genome GERP++ scores greater than 2 (RS score threshold of 2 provides high sensitivity while still strongly enriching for truly constrained sites. )<\/td>20120621<\/td><\/tr>\n
gme<\/td>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)<\/td>20161024<\/td><\/tr>\n
gnomad211_exome<\/td>gnomAD exome collection (v2.1.1), with \u00abAF 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\u00bb header<\/td>20190318<\/td><\/tr>\n
gnomad312_genome<\/td>version 3.1.2 whole-genome data<\/td>20221228<\/td><\/tr>\n
gwava<\/td>whole genome GWAVA_region_score and GWAVA_tss_score (GWAVA_unmatched_score has bug in file), see ref.<\/td>20150623<\/td><\/tr>\n
hrcr1<\/td>40 million variants from 32K samples in haplotype reference consortium<\/td>20151203<\/td><\/tr>\n
icgc28<\/td>International Cancer Genome Consortium version 28<\/td>20210122<\/td><\/tr>\n
intervar_20180118<\/td>InterVar: clinical interpretation of missense variants (indels not supported)<\/td>20180325<\/td><\/tr>\n
kaviar_20150923<\/td>170 million Known VARiants from 13K genomes and 64K exomes in 34 projects<\/td>20151203<\/td><\/tr>\n
knownGene<\/td>FASTA sequences for all annotated transcripts in UCSC Known Gene (last update was 2009-05-10 at UCSC)<\/td>20211019<\/td><\/tr>\n
ljb26_all<\/td>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<\/td>20140925<\/td><\/tr>\n
mcap13<\/td>[M-CAP scores v1.3]<\/td>20181203<\/td><\/tr>\n
mitimpact2<\/td>pathogenicity predictions of human mitochondrial missense variants (see here<\/td>20150520<\/td><\/tr>\n
nci60<\/td>NCI-60 human tumor cell line panel exome sequencing allele frequency data<\/td>20130724<\/td><\/tr>\n
popfreq_all_20150413<\/td>A database containing all allele frequency from 1000G, ESP6500, ExAC and CG46<\/td>20150413<\/td><\/tr>\n
popfreq_max_20150413<\/td>A database containing the maximum allele frequency from 1000G, ESP6500, ExAC and CG46<\/td>20150413<\/td><\/tr>\n
refGene<\/td>FASTA sequences for all annotated transcripts in RefSeq Gene (last update was 2020-08-22 at UCSC)<\/td>20211019<\/td><\/tr>\n
refGeneWithVer<\/td>FASTA sequences for all annotated transcripts in RefSeq Gene with version number (last update was 2020-08-22 at UCSC)<\/td>20211019<\/td><\/tr>\n
regsnpintron<\/td>lifeOver of above<\/td>20180922<\/td><\/tr>\n
regsnpintron<\/td>prioritize the disease-causing probability of intronic SNVs<\/td>20180920<\/td><\/tr>\n
revel<\/td>REVEL scores for non-synonymous variants<\/td>20161205<\/td><\/tr>\n
snp138<\/td>I lifted over SNP138 to hg18<\/td>20140910<\/td><\/tr>\n<\/table>\n