Evidence map›Paper›PMID 27183439›Full record

ArticleNature methods2016

Clonal genotype and population structure inference from single-cell tumor sequencing.

Andrew Roth, Andrew McPherson, Emma Laks, Justina Biele, Damian Yap, Adrian Wan, Maia A Smith, Cydney B Nielsen, Jessica N McAlpine, Samuel Aparicio and 2 more

Abstract read
PubMed Publisher
In one paragraph

Article in Nature methods, 2016. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 68 papers.

0numbers the graph read from it
0cells of the map it votes in
68citing 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

68 citing papers in PubMed.

  1. Article
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  10. Testing for Phylogenetic Signal in Single-Cell RNA-Seq Data.Journal of computational biology : a journal of computational molecular cell biology · 2023
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  13. Review
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8 more citing papers are in PubMed but not listed here.

4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

12 authors.

Andrew RothDepartment of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada.
Andrew McPhersonDepartment of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada.ORCID 0000-0002-5654-5101
Emma LaksDepartment of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada.
Justina BieleDepartment of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada.
Damian YapDepartment of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada.ORCID 0000-0002-5370-4592
Adrian WanDepartment of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada.
Maia A SmithDepartment of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada.
Cydney B NielsenDepartment of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada.
Jessica N McAlpineDepartment of Gynecology and Obstetrics, University of British Columbia, Vancouver, British Columbia, Canada.
Samuel AparicioDepartment of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada.
Alexandre Bouchard-CôtéDepartment of Statistics, University of British Columbia, Vancouver, British Columbia, Canada.
Sohrab P ShahDepartment of Molecular Oncology, BC Cancer Agency, Vancouver, British Columbia, Canada.ORCID 0000-0001-6402-523X

Funding

CIHR FDN-143246CIHR MOP-115170CIHR MSH-261515
6 · The paper itself

Abstract

Single-cell DNA sequencing has great potential to reveal the clonal genotypes and population structure of human cancers. However, single-cell data suffer from missing values and biased allelic counts as well as false genotype measurements owing to the sequencing of multiple cells. We describe the Single Cell Genotyper (https://bitbucket.org/aroth85/scg), an open-source software based on a statistical model coupled with a mean-field variational inference method, which can be used to address these problems and robustly infer clonal genotypes.

Indexed as

SoftwareClone CellsCystadenocarcinoma, SerousFemaleGenome, HumanGenotypeHigh-Throughput Nucleotide SequencingHumansLeukemiaMammary Glands, HumanModels, StatisticalOvarian NeoplasmsPolymorphism, Single NucleotideSingle-Cell Analysis

Identifiers

PMID27183439

What OpenQuestion holds

Textmetadata
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.