Evidence map›Paper›PMID 21546399›Full record

ArticleBioinformatics (Oxford, England)2011

Clonality: an R package for testing clonal relatedness of two tumors from the same patient based on their genomic profiles.

Irina Ostrovnaya, Venkatraman E Seshan, Adam B Olshen, Colin B Begg

Open access · bronzeAbstract read
In one paragraph

Article in Bioinformatics (Oxford, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing papers in PubMed
2.0field-weighted citation impact, top 13% 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

28 citing papers in PubMed, 46 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

4 authors at 2 institutions in 1 country.

Irina OstrovnayaDepartment of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA. ostrovni@mskcc.org
Venkatraman E Seshan
Adam B Olshen
Colin B Begg
Memorial Sloan Kettering Cancer Center · USUniversity of California, San Francisco · US

Funding

Statistical Strategies for Establishing Etiologic Heterogeneity of TumorsR01CA163251 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI BEGG, COLIN B · 2012 to 2015
$1.5M
Statistical Methods for Identifying Clonal TumorsR01CA124504 · NCI · SLOAN-KETTERING INST CAN RESEARCH · PI BEGG, COLIN B · 2009 to 2011
$1.1M
NCI NIH HHS CA124504NCI NIH HHS R01 CA124504NCI NIH HHS R01 CA163251
6 · The paper itself

Abstract

summaryIf a cancer patient develops multiple tumors, it is sometimes impossible to determine whether these tumors are independent or clonal based solely on pathological characteristics. Investigators have studied how to improve this diagnostic challenge by comparing the presence of loss of heterozygosity (LOH) at selected genetic locations of tumor samples, or by comparing genomewide copy number array profiles. We have previously developed statistical methodology to compare such genomic profiles for an evidence of clonality. We assembled the software for these tests in a new R package called 'Clonality'. For LOH profiles, the package contains significance tests. The analysis of copy number profiles includes a likelihood ratio statistic and reference distribution, as well as an option to produce various plots that summarize the results. AVAILABILITY: Bioconductor (http://bioconductor.org/packages/release/bioc/html/Clonality.html) and http://www.mskcc.org/mskcc/html/13287.cfm.

Indexed as

SoftwareClone CellsGenomicsHumansLoss of HeterozygosityNeoplasmsOligonucleotide Array Sequence Analysis

Identifiers

PMID21546399
PMCPMC3106202
OpenAlexW2157759330

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.