↓ Skip to main content

Concordance of copy number alterations using a common analytic pipeline for genome-wide analysis of Illumina and Affymetrix genotyping data: a report from the Children's Oncology Group

Overview of attention for article published in Cancer Genetics, May 2015
Altmetric Badge

About this Attention Score

  • Average Attention Score compared to outputs of the same age
  • Above-average Attention Score compared to outputs of the same age and source (64th percentile)

Mentioned by

twitter
2 X users

Citations

dimensions_citation
3 Dimensions

Readers on

mendeley
19 Mendeley
You are seeing a free-to-access but limited selection of the activity Altmetric has collected about this research output. Click here to find out more.
Title
Concordance of copy number alterations using a common analytic pipeline for genome-wide analysis of Illumina and Affymetrix genotyping data: a report from the Children's Oncology Group
Published in
Cancer Genetics, May 2015
DOI 10.1016/j.cancergen.2015.04.010
Pubmed ID
Authors

Marijana Vujkovic, Edward F. Attiyeh, Rhonda E. Ries, Michelle Horn, Elizabeth K. Goodman, Yang Ding, Marko Kavcic, Todd A. Alonzo, Robert B. Gerbing, Betsy Hirsch, Susana Raimondi, Alan S. Gamis, Soheil Meshinchi, Richard Aplenc

Abstract

Copy number alterations (CNAs) are a hallmark of pediatric cancer genomes. An increasing number of research groups use multiple platforms and software packages to detect and analyze CNAs. However, different platforms have experimental and analysis-specific biases that may yield different results. We sought to estimate the concordance of CNAs in children with de novo acute myeloid leukemia between two experimental platforms: Affymetrix SNP 6.0 array and Illumina OmniQuad 2.5 BeadChip. Forty-five paired tumor-remission samples were genotyped on both platforms, and CNAs were estimated from total signal intensity and allelic contrast values using the allele-specific copy number analysis of tumors (ASCAT) algorithm. The two platforms were comparable in detection of CNAs, each missing only two segments from a total of 42 CNAs (4.6%). Overall, there was an interplatform agreement of 96% for allele-specific tumor profiles. However, poor quality samples with low signal/noise ratios showed a high rate of false-positive segments independent of the genotyping platform. These results demonstrate that a common analytic pipeline can be utilized for SNP array data from these two platforms. The customized programming template for the preprocessing, data integration, and analysis is publicly available at https://github.com/AplenCHOP/affyLumCNA.

X Demographics

X Demographics

The data shown below were collected from the profiles of 2 X users who shared this research output. Click here to find out more about how the information was compiled.
Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 19 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Norway 2 11%
Czechia 1 5%
United Kingdom 1 5%
Unknown 15 79%

Demographic breakdown

Readers by professional status Count As %
Researcher 8 42%
Student > Master 3 16%
Student > Ph. D. Student 2 11%
Other 2 11%
Student > Doctoral Student 1 5%
Other 0 0%
Unknown 3 16%
Readers by discipline Count As %
Agricultural and Biological Sciences 6 32%
Biochemistry, Genetics and Molecular Biology 5 26%
Medicine and Dentistry 3 16%
Psychology 1 5%
Engineering 1 5%
Other 0 0%
Unknown 3 16%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 2. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 27 October 2015.
All research outputs
#15,169,949
of 25,374,917 outputs
Outputs from Cancer Genetics
#799
of 1,174 outputs
Outputs of similar age
#138,595
of 279,171 outputs
Outputs of similar age from Cancer Genetics
#5
of 14 outputs
Altmetric has tracked 25,374,917 research outputs across all sources so far. This one is in the 38th percentile – i.e., 38% of other outputs scored the same or lower than it.
So far Altmetric has tracked 1,174 research outputs from this source. They receive a mean Attention Score of 3.2. This one is in the 31st percentile – i.e., 31% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 279,171 tracked outputs that were published within six weeks on either side of this one in any source. This one is in the 48th percentile – i.e., 48% of its contemporaries scored the same or lower than it.
We're also able to compare this research output to 14 others from the same source and published within six weeks on either side of this one. This one has gotten more attention than average, scoring higher than 64% of its contemporaries.