ArticleBioinformatics advances2026
GDIv2: improving variant selection from human exomes.
Article in Bioinformatics advances, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
0 citing papers in PubMed.
No citing paper in PubMed yet.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors.
Funding
Abstract
Motivation: The Gene Damage Index (GDI) quantifies the cumulative mutational damage of protein-coding genes in the general population and helps prioritize candidate disease genes in sequencing studies. However, the original GDI is influenced by coding sequence length and does not account for gene-specific differences in variant deleteriousness. We developed GDIv2, an updated framework correcting for coding sequence length and incorporating gene-specific normalization of CADD scores to improve discrimination between disease-relevant and non-relevant genes. Results: Four GDIv2 implementations were generated using 1000 Genomes Project and gnomAD datasets for both GRCh37 and GRCh38 genome builds. Benchmarking against the original GDI showed that all GDIv2 versions significantly improved discrimination between relevant and accessory genes, reduced erroneous exclusion of relevant genes, and increased exclusion of accessory genes. GDIv2_1kGP_37 achieved the best AUC performance and excluded 24.6% of accessory genes while retaining 96.7% of relevant genes. Compared with RVIS, LOEUF, s Availability and implementation: GDIv2 resources are freely available at https://hgidsoft.rockefeller.edu/GDI/GDIv2.html.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.