Experiments
Searchable full-text extractions: founding hypothesis, core claims, experimental setups, key results and statistics — pulled out of each paper as structure. Search a cell line, an assay or an entity (e.g. HUH7) and find every paper that worked with it. This corpus stands on its own: most entries carry no reproduction assessment (yet).
-
Has reproduction · 76
Correcting scale distortion in RNA sequencing data.
PMID 39875825 · PMC11776150 · BMC bioinformatics · 2025 · 8 claims · 8 setups
Local averaging reveals expression-level-dependent biases that differ from sample to sample across all RNA-seq datasets studied, and are not corrected by conventional normalization (TPM/FPKM)
-
Full-text index only
Tractor workflow: a scalable Nextflow framework for local ancestry-aware genome-wide association studies.
PMID 41838407 · PMC13197121 · Bioinformatics (Oxford, England) · 2026 · 7 claims · 6 setups
Developed a scalable Nextflow workflow that automates phasing, local ancestry inference (LAI), and Tractor GWAS into a reproducible end-to-end pipeline
-
Full-text index only
Getting knit-PI3Ky: PIK3CA mutation status to direct multimodality therapy?
PMID 19903790 · PMC3400141 · Clinical cancer research : an official journal of the American Association for Cancer Research · 2009 · 8 claims · 1 setups
PIK3CA mutations are associated with local disease recurrence in rectal cancer patients
-
Full-text index only
Six new loci associated with blood low-density lipoprotein cholesterol, high-density lipoprotein cholesterol or triglycerides in humans.
PMID 18193044 · PMC2682493 · Nature genetics · 2008 · 8 claims · 7 setups
GWAS plus targeted replication identified 18 loci reproducibly associated with LDL cholesterol, HDL cholesterol, and/or triglycerides, six of which are newly identified
-
Has reproduction
Fast, accurate, and racially unbiased pan-cancer tumor-only variant calling with tabular machine learning.
PMID 36611079 · PMC9825621 · NPJ precision oncology · 2023 · 8 claims · 8 setups
Tree-based (XGBoost, LightGBM) and deep-learning (TabNet) tabular ML classifiers achieve state-of-the-art somatic vs germline classification in tumor-only WES samples, outperforming PureCN.