Protocol for using GRPath to identify putative gene regulation paths in complex human diseases.

Xi Xi, Haochen Li, Lei Wei, Xuegong Zhang

Open access · goldAbstract read

In one paragraph

Article in STAR protocols, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it

0cells of the map it votes in

1citing papers in PubMed

0.1field-weighted citation impact, top 56% of its field

1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

1 citing paper in PubMed, 1 citations in OpenAlex.

scTML: a pan-cancer single-cell landscape of multiple mutation types.Nucleic acids research · 2025
Article

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

4 authors at 1 institution in 1 country.

Xi XiMOE Key Laboratory of Bioinformatics and Bioinformatics Division, BNRIST/Department of Automation, Tsinghua University, Beijing 100084, China. Electronic address: xix19@mails.tsinghua.edu.cn.

Haochen LiSchool of Medicine, Tsinghua University, Beijing 100084, China.

Lei WeiMOE Key Laboratory of Bioinformatics and Bioinformatics Division, BNRIST/Department of Automation, Tsinghua University, Beijing 100084, China.

Xuegong ZhangMOE Key Laboratory of Bioinformatics and Bioinformatics Division, BNRIST/Department of Automation, Tsinghua University, Beijing 100084, China; School of Medicine, Tsinghua University, Beijing 100084, China. Electronic address: zhangxg@tsinghua.edu.cn.

Tsinghua University · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Unfolding the "black-box" associations between genotype and phenotype is essential for understanding the molecular mechanisms of complex human diseases. Here, we describe the use of GRPath to uncover putative causal paths (pcPaths) from genetic variants to disease phenotypes. GRPath takes multiple omics data and summary statistics as input and identifies pcPaths that link the putative causal region (pcRegion), putative causal variant (pcVariant), putative causal gene (pcGene), noteworthy cell type, and disease phenotype. For complete details on the use and execution of this protocol, please refer to Xi et al. (2022).

Indexed as

Gene Expression RegulationGenome-Wide Association StudyCausalityGenotypeHumansPhenotypeBioinformaticsGene ExpressionHealth SciencesRNAseqSingle CellSystems biology

Identifiers

PMID36386883

DOI10.1016/j.xpro.2022.101831

PMCPMC9664398

OpenAlexW4308655547

What OpenQuestion holds

Textmetadata

LicenceCC BY-NC-ND

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Registered trials

None linked

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.