Evidence map›Paper›PMID 22023820›Full record

ArticleGenome biology2011

Allele-specific copy number analysis of tumor samples with aneuploidy and tumor heterogeneity.

Markus Rasmussen, Magnus Sundström, Hanna Göransson Kultima, Johan Botling, Patrick Micke, Helgi Birgisson, Bengt Glimelius, Anders Isaksson

Abstract read
In one paragraph

Article in Genome biology, 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 54 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
54citing papers in PubMed, 1 pooled it
–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

54 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
  2. Transcriptomic Subgroups in Soft Tissue Tumors Correlate with Morphologic Subtype, Genomic Features, and Outcome.Clinical cancer research : an official journal of the American Association for Cancer Research · 2026
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  11. Resolving the Pathogenesis of Anaplastic Wilms Tumors through Spatial Mapping of Cancer Cell Evolution.Clinical cancer research : an official journal of the American Association for Cancer Research · 2023
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  15. The diagnostic utility of DNA copy number analysis of core needle biopsies from soft tissue and bone tumors.Laboratory investigation; a journal of technical methods and pathology · 2022
    Article
  16. Article
  17. Computational and structural biotechnology journal · 2022
    Article
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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

8 authors.

Markus RasmussenScience for Life Laboratory, Department of Medical Sciences, Uppsala University, Akademiska sjukhuset, SE-751 85 Uppsala, Sweden.
Magnus Sundström
Hanna Göransson Kultima
Johan Botling
Patrick Micke
Helgi Birgisson
Bengt Glimelius
Anders Isaksson

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

We describe a bioinformatic tool, Tumor Aberration Prediction Suite (TAPS), for the identification of allele-specific copy numbers in tumor samples using data from Affymetrix SNP arrays. It includes detailed visualization of genomic segment characteristics and iterative pattern recognition for copy number identification, and does not require patient-matched normal samples. TAPS can be used to identify chromosomal aberrations with high sensitivity even when the proportion of tumor cells is as low as 30%. Analysis of cancer samples indicates that TAPS is well suited to investigate samples with aneuploidy and tumor heterogeneity, which is commonly found in many types of solid tumors.

Indexed as

AllelesAneuploidyGene DosageGenes, NeoplasmSoftwareAbnormal KaryotypeAlgorithmsCell Line, TumorColonic NeoplasmsComputational BiologyGenetic HeterogeneityHumansOligonucleotide Array Sequence AnalysisPolymorphism, Single NucleotideSensitivity and Specificity

Identifiers

PMID22023820
PMCPMC3333778

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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.