Evidence map›Paper›PMID 34343239›Full record

ArticleBriefings in bioinformatics2021

Tracing the evolution of aneuploid cancers by multiregional sequencing with CRUST.

Subhayan Chattopadhyay, Jenny Karlsson, Anders Valind, Natalie Andersson, David Gisselsson

Open access · hybridAbstract read
In one paragraph

Article in Briefings in bioinformatics, 2021. 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 62% 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.

  1. 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

5 authors at 1 institution in 1 country.

Subhayan ChattopadhyayDivision of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden.ORCID 0000-0002-8599-2971
Jenny KarlssonDivision of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden.
Anders ValindDivision of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden.
Natalie AnderssonDivision of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden.
David GisselssonDivision of Clinical Genetics, Department of Laboratory Medicine, Lund University, Lund, Sweden.
Lund University · SE

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Clonal deconvolution of mutational landscapes is crucial to understand the evolutionary dynamics of cancer. Two limiting factors for clonal deconvolution that have remained unresolved are variation in purity and chromosomal copy number across different samples of the same tumor. We developed a semi-supervised algorithm that tracks variant calls through multi-sample spatiotemporal tumor data. While normalizing allele frequencies based on purity, it also adjusts for copy number changes at clonal deconvolution. Absent à priori copy number data, it renders in silico copy number estimations from bulk sequences. Using published and simulated tumor sequences, we reliably segregated clonal/subclonal variants even at a low sequencing depth (~50×). Given at least one pure tumor sample (>70% purity), we could normalize and deconvolve paired samples down to a purity of 40%. This renders a reliable clonal reconstruction well adapted to multi-regionally sampled solid tumors, which are often aneuploid and contaminated by non-cancer cells.

Indexed as

AneuploidyEvolution, MolecularAlgorithmsComputer SimulationDatasets as TopicDNA Copy Number VariationsGene FrequencyHumansMutationNeoplasmsclonal deconvolutionmultiregional sequencingphylogenysubclonal reconstruction

Identifiers

PMID34343239
PMCPMC8981300
OpenAlexW3187984642

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

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.