Linking regulatory variants to target genes by integrating single-cell multiome methods and genomic distance

SNP-gene link predictions associated with our paper titled "Linking regulatory variants to target genes by integrating single-cell multiome methods and genomic distance," generated by pgBoost and constituent methods SCENT (Sakaue et al. 2024 Nat Genet), Signac (Stuart et al. 2021 Nat Methods), ArchR (Granja et al. 2021 Nat Genet), and Cicero (Pliner et al. 2018 Mol Cell).

pgBoost_scores.tsv.gz contains linking predictions made by pgBoost.

constituent_method_scores.tsv.gz contains linking predictions made by constituent methods.

Linking scores and percentiles are reported for each method (pgBoost score, SCENT FDR, Signac correlation, ArchR correlation, Cicero co-accessibility). Rank percentiles are computed as: 1 - (rank / n). When multiple links receive the same score, they are assigned the percentile of the top rank. Links unscored by each method (denoted by zeros* in the linking score column) are assigned a percentile equivalent to the percent of links unscored by the focal method. See the Methods section of the paper for further details on computing linking scores and summarizing scores across cell types and data sets.

*Candidate links tested and assigned a co-accessibility of zero by the Cicero method are given a score of 1e-100 in the "Cicero" column to distinguish between unscored candidate links and candidate links assigned a co-accessibility of zero (see Pliner et al. 2018 Mol Cell).