EPD's 40th Anniversary Symposium is open for registration !!! (click here)
(taking place in Geneva on Sep 4 2026, just after
ECCB 2026,
for more information, see https://epd.expasy.org/EPD_symposium2026/)
SNP2TFBS is a Web interface aimed at studying variations (SNPs/indels) that affect transcription factor binding (TFB) in the Human genome.
The resource is based on a new 'in silico' approach for identifying regulatory variants. Here, we compute the PWM score in both reference (hg19) and alternate human genome assemblies. The alternate genome assembly is generated by incorporating the alternate allele of common genetic variants (AF≥0.001) from 1000 Genomes project. If there are multiple alleles for a variant, we incorporate the most common allele.
Putative TF binding sites computed from these two genome assemblies are merged. One can then select interesting variants, e.g. SNPs that are missing in the reference PWM matches but increase the PWM score (above the minimum) in the alternate assembly.
SNP2TFBS includes the following tools:
- SNPViewer, a Web service used to query SNPs by their rsID identifier for examining variations that affect regions of transcription factor binding. It outputs a table that lists all the factors whose binding sites are significantly affected by the variant in question.
- SNSelect, a set of tools for selecting and visualizing user defined variants that affect single or multiple TFs. Users may upload lists of variants in two different formats, rsID and VCF, or upload lists of genomic regions, or else select a specific TF PWM or a gene name. Output includes variant annotation plots and TF enrichment graphs that allow users to easily visualize the most affected factors against their variants. Variants are annotated based on their context.
- PWMViewer, a tool for displaying information about the factor models that have been used to score the transcription factor binding sites (TFBSs). The PWM library used by SNP2TFBS is JASPAR CORE 2014 (vertebrates).
The SNP2TFBS FTP repository contains data files in multiple formats that can be downloaded for further analysis. Supported file formats include BED, annotated and tab-delimited text. Variant annotation is carried out using ANNOVAR input (hg19_refGene).
