A large‐scale exome array analysis of venous thromboembolism is a research paper published in Genetic Epidemiology (2019). On theSindex it has a DataRank of 1.4. It has been cited 27 times, with 22 citing works in its 1-hop citation network.
AbstractAlthough recent Genome‐Wide Association Studies have identified novel associations for common variants, there has been no comprehensive exome‐wide search for low‐frequency variants that affect the risk of venous thromboembolism (VTE). We conducted a meta‐analysis of 11 studies comprising 8,332 cases and 16,087 controls of European ancestry and 382 cases and 1,476 controls of African American ancestry genotyped with the Illumina HumanExome BeadChip. We used the seqMeta package in R to conduct single variant and gene‐based rare variant tests. In the single variant analysis, we limited our analysis to the 64,794 variants with at least 40 minor alleles across studies (minor allele frequency [MAF] ~0.08%). We confirmed associations with previously identified VTE loci, including ABO, F5, F11, and FGA. After adjusting for multiple testing, we observed no novel significant findings in single variant or gene‐based analysis. Given our sample size, we had greater than 80% power to detect minimum odds ratios greater than 1.5 and 1.8 for a single variant with MAF of 0.01 and 0.005, respectively. Larger studies and sequence data may be needed to identify novel low‐frequency and rare variants associated with VTE risk.
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Base Score Contribution
0.500
From this paper's citation signal
Citation Network Contribution
0.933
From 18 citing papers with measurable signal
Ranked by citation count — the same ordering the engine uses when summing log1p(Cq) over citers.
DataRank blends this paper's own citation count with the influence of the papers that cite it. Here, roughly 35% comes from its base citations and 65% from the citation network (18 citing papers contributed measurable signal).
Citers are pulled from OpenAlex sorted by cited_by_count:descand capped per paper, so when the cap binds we keep the highest-signal references and the score is reproducible across reruns.
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