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

<p>The below data are associated with our paper entitled "Linking regulatory variants to target genes by integrating single-cell multiome methods and genomic distance."</p> <p>1) SNP-gene link predictions generated by pgBoost and existing methods SCENT (Sakaue et al. 2024 <em>Nat Genet</em>), Signac (Stuart et al. 2021 <em>Nat Methods</em>), ArchR (Granja et al. 2021 <em>Nat Genet</em>), and Cicero (Pliner et al. 2018 <em>Mol Cell</em>).</p> <p><strong>pgBoost_scores.tsv.gz </strong>contains linking predictions made by pgBoost.</p> <p><strong>constituent_method_scores.tsv.gz</strong> contains linking predictions made by constituent methods.</p> <p><em><span>**NOTE: promoters (+/- 1kb from TSS) and candidate links &gt;500kb are excluded from linking predictions (see manuscript)**</span></em></p> <p>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.</p> <p>*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 partial correlation of zero (see Pliner et al. 2018 <em>Mol Cell</em>).</p> <p><em>NOTE: The predictions associated with this release (version 2) were generated using an expanded set of data sets, an expanded training set, and corrected TSS coordinates.</em></p> <p>2) GWAS-derived evaluation SNP-gene link evaluation set.</p> <p><strong>gwas_evaluation.tsv</strong>: GWAS-derived evaluation SNP-gene link evaluation set. Column 1 provides SNP coordinates in the format &lt;chr-start-end&gt;. This evaluation framework was proposed by Weeks et al. 2024 <em>Nature Genetics</em> based on fine-mapping results from Kanai et al. <em>medrxiv</em>&nbsp;(see Methods: <em>Evaluation data sets</em> of Dorans et al.). "True" links (gold = 1) are non-coding variants fine-mapped to a focal trait (PIP &gt; 0.1) with a coding variant for exactly one candidate gene within 1 Mb&nbsp;attaining PIP &gt; 0.5 for the same trait. "False" links (gold = 0) are candidate SNP-gene pairs involving a SNP with a "true" link. This file of SNP-gene links was adapted from credible set-gene links <a href="https://github.com/Deylab999/GWAS_benchmark_IGVF/blob/bb91d08cc02d59cdd829eb1430569057ac26c5fe/V2G/ENCODE_E2G_2023/UKBiobank.ABCGene.anyabc.tsv">here</a> (the "truth" column defines true/false links) by identifying SNPs with PIP &gt; 0.1 within each credible set-gene link.</p>

ShareScore

40/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
4
Harmonization
4
Access
20
Reuse readiness
8
Engagement
4