Evidence map›Paper›PMID 34816127›Full record

ArticleSTAR protocols2021

Identifying tumorigenic non-coding mutations through altered

Zhongshan Cheng, Michael Vermeulen, Micheal Rollins-Green, Tomas Babak, Brian DeVeale

Abstract read
In one paragraph

Article in STAR protocols, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

5 authors.

Zhongshan ChengDepartment of Biology, Queen's University, Kingston, ON K7L 3N6, Canada.
Michael VermeulenDepartment of Biology, Queen's University, Kingston, ON K7L 3N6, Canada.
Micheal Rollins-GreenDepartment of Biology, Queen's University, Kingston, ON K7L 3N6, Canada.
Tomas BabakDepartment of Biology, Queen's University, Kingston, ON K7L 3N6, Canada.
Brian DeVealeThe Eli and Edythe Broad Center of Regeneration Medicine and Stem Cell Research, University of California, San Francisco, San Francisco, CA 94143, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Identification of non-coding mutations driving tumorigenesis requires alternative approaches to coding mutations. Enriched associations between mutated regulatory elements and altered cis-regulation in tumors are a promising approach to stratify candidate non-coding driver mutations. Here we provide a bioinformatics pipeline to mine data from the Cancer Genomic Commons (GDC) for such associations. The pipeline integrates RNA and whole-genome sequencing with genotyping data to reveal putative non-coding driver mutations by cancer type. For complete information on the generation and use of this protocol, please refer to Cheng et al. (2021).

Indexed as

CarcinogenesisComputational BiologyDatabases, GeneticHumansMutationNeoplasmsRegulatory Sequences, Nucleic AcidBioinformaticsCancerGenomicsRNAseqSequence analysis

Identifiers

PMID34816127
PMCPMC8591365

What OpenQuestion holds

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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.