Evidence map›Paper›PMID 34910733›Full record

ArticlePLoS computational biology2021

Statistical tests for intra-tumour clonal co-occurrence and exclusivity.

Jack Kuipers, Ariane L Moore, Katharina Jahn, Peter Schraml, Feng Wang, Kiyomi Morita, P Andrew Futreal, Koichi Takahashi, Christian Beisel, Holger Moch and 1 more

Open access · goldAbstract read
In one paragraph

Article in PLoS computational biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.

0numbers the graph read from it
0cells of the map it votes in
6citing papers in PubMed
0.9field-weighted citation impact, top 31% 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

6 citing papers in PubMed, 14 citations in OpenAlex.

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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

11 authors at 4 institutions in 2 countries.

Jack KuipersDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.ORCID 0000-0001-5357-2705
Ariane L MooreDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.ORCID 0000-0001-7831-5115
Katharina JahnDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.ORCID 0000-0002-6983-4615
Peter SchramlDepartment of Pathology and Molecular Pathology, University and University Hospital Zurich, Zurich, Switzerland.ORCID 0000-0002-0087-2744
Feng WangDepartment of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Kiyomi MoritaDepartment of Leukemia, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.ORCID 0000-0002-0407-1565
P Andrew FutrealDepartment of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.
Koichi TakahashiDepartment of Genomic Medicine, The University of Texas MD Anderson Cancer Center, Houston, Texas, United States of America.ORCID 0000-0002-8027-9659
Christian BeiselDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.
Holger MochDepartment of Pathology and Molecular Pathology, University and University Hospital Zurich, Zurich, Switzerland.
Niko BeerenwinkelDepartment of Biosystems Science and Engineering, ETH Zurich, Basel, Switzerland.ORCID 0000-0002-0573-6119
SIB Swiss Institute of Bioinformatics · CHThe University of Texas MD Anderson Cancer Center · USUniversity Hospital of Zurich · CHETH Zurich · CH

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Tumour progression is an evolutionary process in which different clones evolve over time, leading to intra-tumour heterogeneity. Interactions between clones can affect tumour evolution and hence disease progression and treatment outcome. Intra-tumoural pairs of mutations that are overrepresented in a co-occurring or clonally exclusive fashion over a cohort of patient samples may be suggestive of a synergistic effect between the different clones carrying these mutations. We therefore developed a novel statistical testing framework, called GeneAccord, to identify such gene pairs that are altered in distinct subclones of the same tumour. We analysed our framework for calibration and power. By comparing its performance to baseline methods, we demonstrate that to control type I errors, it is essential to account for the evolutionary dependencies among clones. In applying GeneAccord to the single-cell sequencing of a cohort of 123 acute myeloid leukaemia patients, we find 1 clonally co-occurring and 8 clonally exclusive gene pairs. The clonally exclusive pairs mostly involve genes of the key signalling pathways.

Indexed as

Leukemia, Myeloid, AcuteAlgorithmsComputational BiologyDisease ProgressionHumansModels, StatisticalMutationSignal Transduction

Identifiers

PMID34910733
PMCPMC8716063
OpenAlexW4200546528

What OpenQuestion holds

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Registered trials

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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.