2026-10-15T01:02:56Z https://www.scidb.cn/oai

10.57760/sciencedb.0140t 2026-09-29T15:09:26Z

2026-09-29 Analysis code for "Germline causality is not tumour prognosis: dissecting the genetic and prognostic architecture of colorectal cancer in the COADREAD cohort" doi:10.57760/sciencedb.0140t en This dataset contains the complete analysis code underlying the manuscript "Germline causality is not tumour prognosis: dissecting the genetic and prognostic architecture of colorectal cancer in the COADREAD cohort". The study separates two axes that are routinely fused into a single score: the germline causal axis (whether a gene influences the risk of developing colorectal cancer) and the tumour prognostic axis (whether the expression of that gene in the tumour predicts patient outcome). A 267-gene SNP-related gene set was built by mapping 84 independent risk loci to genes; this set constrained the development of an eight-gene prognostic signature, which was validated across seven external cohorts. A cis-expression quantitative trait locus Mendelian randomisation scan with colocalisation, HEIDI gating, robustness testing (outlier instruments, multivariable Mendelian randomisation, signal-level colocalisation) and druggability assessment was then performed. The archive contains 60 analysis scripts covering preprocessing, genome-wide association study quality control, SNP-to-gene mapping, prognostic modelling, external validation, Mendelian randomisation, colocalisation and figure generation; download helpers for public genome-wide association summary statistics, expression quantitative trait locus resources and Gene Expression Omnibus series; and query scripts for Open Targets, DGIdb, the Human Protein Atlas and the protein quantitative trait locus catalogue. The code is written in R 4.5.3 with a small amount of Python 3.13 for download and query utilities. No third-party dataset is redistributed: all inputs are publicly available and must be obtained from their original sources, as listed in the accompanying README. The analyses used only publicly available summary-level statistics and previously published de-identified data, so ethical approval and informed consent were not required. A single parameter must be edited before running the code: the project root constant BASE at the top of analysis_code/00_core_functions.R. All other paths are derived from it. The random seed is 20260908. colorectal cancer; COADREAD cohort; Mendelian randomisation Xiao Peng Tao Angui Meng Jizeng Jin Bo Liu Jianhui PUBLIC https://api.github.com/licenses/mit dataset Science Data Bank