FAVOR: functional annotation of variants online resource and annotator for variation across the human genome

Abstract

Large biobank-scale whole genome sequencing (WGS) studies are rapidly identifying a multitude of coding and non-coding variants. They provide an unprecedented resource for illuminating the genetic basis of human diseases. Variant functional annotations play a critical role in WGS analysis, result interpretation, and prioritization of disease- or trait-associated causal variants. Existing functional annotation databases have limited scope to perform online queries and functionally annotate the genotype data of large biobank-scale WGS studies. We develop the Functional Annotation of Variants Online Resources (FAVOR) to meet these pressing needs. FAVOR provides a comprehensive multi-faceted variant functional annotation online portal that summarizes and visualizes findings of all possible nine billion single nucleotide variants (SNVs) across the genome. It allows for rapid variant-, gene- and region-level queries of variant functional annotations. FAVOR integrates variant functional information from multiple sources to describe the functional characteristics of variants and facilitates prioritizing plausible causal variants influencing human phenotypes. Furthermore, we provide a scalable annotation tool, FAVORannotator, to functionally annotate large-scale WGS studies and efficiently store the genotype and their variant functional annotation data in a single file using the annotated Genomic Data Structure (aGDS) format, making downstream analysis more convenient. FAVOR and FAVORannotator are available at https://favor.genohub.org.

The sequence kernel association test for multicategorical outcomes

“…Second, besides assigning weights based on minor allele frequencies, the weights for rare variants can be assigned by incorporating functional annotations. The commonly used annotation weights include annotation principal components (X. Li et al, 2020; Zhou et al, 2023), CADD (Kircher et al, 2014; Rentzsch et al, 2019), MACIE (X. Li, Yung, et al, 2022), among others (Gaynor et al, 2022; P. H. Lee, Lee, et al, 2018). Last, using summary statistics in SKAT‐MC.…”

“…The commonly used annotation weights include annotation principal components (X. Li et al, 2020;Zhou et al, 2023), CADD (Kircher et al, 2014;Rentzsch et al, 2019), MACIE (X. Li, Yung, et al, 2022), among others (Gaynor et al, 2022;.…”

GPN-MSA: an alignment-based DNA language model for genome-wide variant effect prediction

“…To investigate whether GPN-MSA captures any functional impact of a variant, we performed functional enrichment analysis separately on four datasets curated across four public variant interpretation databases, ClinVar, COSMIC, OMIM and gnomAD. We used 18 functional annotations obtained from the FAVOR database [39] (accessed via Harvard Dataverse on April 10, 2023), which measure both impact of natural selection and gene regulatory activity of a variant (see Supplementary Table S2). For clarity, we collect computational details of the functional annotations and summarize them below.…”

Deciphering the causal relationship between blood pressure and regional white matter integrity: A two‐sample Mendelian randomization study

“…Lastly (iii), we performed conditional independence tests to exclude IVs with evidence of horizontal pleiotropy (FDR‐adjusted p ‐value >.1). In addition to satisfying the standard IV assumptions, we also followed more recent guidance for IV selection from Burgess et al (2019) to select IVs that more biologically relevant to the exposure by performing the following steps: We first functionally annotated the IVs using an open‐access online portal FAVOR (Functional Annotation of Variants; https://favor.genohub.org/) (Zhou et al, 2023). We then confined to those IVs with a biological link to BP reported in all published human GWAS studies collected by the NIH National Human Genome Research Institute GWAS catalogue (Buniello et al, 2019) through querying their corresponding functional annotations.…”