Evidence map›Paper›PMID 33622385›Full record

ArticleGenome biology2021

MEDALT: single-cell copy number lineage tracing enabling gene discovery.

Fang Wang, Qihan Wang, Vakul Mohanty, Shaoheng Liang, Jinzhuang Dou, Jincheng Han, Darlan Conterno Minussi, Ruli Gao, Li Ding, Nicholas Navin and 1 more

Abstract read
In one paragraph

Article in Genome biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 29 papers.

0numbers the graph read from it
0cells of the map it votes in
29citing 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

29 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Review
  5. Cell lineage tracing: Methods, applications, and challenges.Quantitative biology (Beijing, China) · 2025
    Review
  6. Article
  7. Article
  8. Review
  9. Article
  10. Article
  11. Article
  12. Article
  13. Article
  14. Review
  15. Article
  16. Review
  17. Review
  18. Review
  19. Article
  20. 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

11 authors.

Fang Wang *Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Houston, TX, USA.
Qihan Wang *Department of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Houston, TX, USA.
Vakul MohantyDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Houston, TX, USA.
Shaoheng LiangDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Houston, TX, USA.
Jinzhuang DouDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Houston, TX, USA.
Jincheng HanDepartment of Cancer Biology, The University of Texas MD Anderson Cancer Center, Houston, USA.
Darlan Conterno MinussiDepartment of Genetics, The University of Texas MD Anderson Cancer Center, Houston, USA.
Ruli GaoDepartment of Cardiovascular Sciences, Center for Bioinformatics and Computational Biology, Houston Methodist Research Institute, Houston, USA.
Li DingDepartment of Medicine, McDonnell Genome Institute Washington University School of Medicine, St. Louis, USA.
Nicholas NavinDepartment of Genetics, The University of Texas MD Anderson Cancer Center, Houston, USA.
Ken ChenDepartment of Bioinformatics and Computational Biology, The University of Texas MD Anderson Cancer Center, 1400 Pressler St, Houston, TX, USA. kchen3@mdanderson.org.ORCID 0000-0003-4013-5279

Funding

Tumor Evolution and Metastasis ProgramP30CA016672 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI Scott Kopetz · 1985 to 2026
$290.8M
Systems-Based Predictions of Responses to Cancer TherapyU54CA112970 · NCI · UNIVERSITY OF CALIF-LAWRENC BERKELEY LAB · PI MILLS, GORDON B. · 2004 to 2014
$27.1M
Integrative bioinformatics and functional characterization of oncogenic driver aberrations in cancerU01CA217842 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI DENEEN, BENJAMIN, MILLS, GORDON B. · 2017 to 2021
$3.6M
Delineating Heterogeneous Structural Complexity in Cancer GenomesR01CA172652 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI CHEN, KEN · 2013 to 2016
$1.4M
Informatics for Functional Integration of Heterogeneous Cancer Genome and Transcriptome Sequencing DataU01CA247760 · NCI · UNIVERSITY OF TX MD ANDERSON CAN CTR · PI CHEN, KEN · 2020 to 2022
$1.2M
NCI NIH HHS P30 CA016672NCI NIH HHS U01 CA217842NCI NIH HHS U01 CA247760NCI NIH HHS U54 CA112970NIH HHS R01CA172652NIH HHS U01CA211006NIH HHS U01CA247760
6 · The paper itself

Abstract

We present a Minimal Event Distance Aneuploidy Lineage Tree (MEDALT) algorithm that infers the evolution history of a cell population based on single-cell copy number (SCCN) profiles, and a statistical routine named lineage speciation analysis (LSA), whichty facilitates discovery of fitness-associated alterations and genes from SCCN lineage trees. MEDALT appears more accurate than phylogenetics approaches in reconstructing copy number lineage. From data from 20 triple-negative breast cancer patients, our approaches effectively prioritize genes that are essential for breast cancer cell fitness and predict patient survival, including those implicating convergent evolution.The source code of our study is available at https://github.com/KChen-lab/MEDALT .

Indexed as

AneuploidyGene DosageRNA-SeqSingle-Cell AnalysisSoftwareAlgorithmsComputational BiologyEvolution, MolecularGenetic Association StudiesGenetic FitnessGenetic Predisposition to DiseaseHigh-Throughput Nucleotide SequencingHumansCopy number alterationDriver discoveryLineage tracingscDNA-seqscRNA-seqSingle-cellTumor evolution

Identifiers

PMID33622385
PMCPMC7901082

What OpenQuestion holds

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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.