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Detect tissue heterogeneity in gene expression data with BioQC

Overview of attention for article published in BMC Genomics, April 2017
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  • Good Attention Score compared to outputs of the same age and source (72nd percentile)

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3 X users
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1 Wikipedia page

Citations

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49 Dimensions

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35 Mendeley
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Title
Detect tissue heterogeneity in gene expression data with BioQC
Published in
BMC Genomics, April 2017
DOI 10.1186/s12864-017-3661-2
Pubmed ID
Authors

Jitao David Zhang, Klas Hatje, Gregor Sturm, Clemens Broger, Martin Ebeling, Martine Burtin, Fabiola Terzi, Silvia Ines Pomposiello, Laura Badi

Abstract

Gene expression data can be compromised by cells originating from other tissues than the target tissue of profiling. Failures in detecting such tissue heterogeneity have profound implications on data interpretation and reproducibility. A computational tool explicitly addressing the issue is warranted. We introduce BioQC, a R/Bioconductor software package to detect tissue heterogeneity in gene expression data. To this end BioQC implements a computationally efficient Wilcoxon-Mann-Whitney test and provides more than 150 signatures of tissue-enriched genes derived from large-scale transcriptomics studies. Simulation experiments show that BioQC is both fast and sensitive in detecting tissue heterogeneity. In a case study with whole-organ profiling data, BioQC predicted contamination events that are confirmed by quantitative RT-PCR. Applied to transcriptomics data of the Genotype-Tissue Expression (GTEx) project, BioQC reveals clustering of samples and suggests that some samples likely suffer from tissue heterogeneity. Our experience with gene expression data indicates a prevalence of tissue heterogeneity that often goes unnoticed. BioQC addresses the issue by integrating prior knowledge with a scalable algorithm. We propose BioQC as a first-line tool to ensure quality and reproducibility of gene expression data.

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X Demographics

The data shown below were collected from the profiles of 3 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 35 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Germany 1 3%
Unknown 34 97%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 8 23%
Researcher 6 17%
Student > Bachelor 4 11%
Student > Doctoral Student 2 6%
Student > Postgraduate 2 6%
Other 5 14%
Unknown 8 23%
Readers by discipline Count As %
Biochemistry, Genetics and Molecular Biology 8 23%
Agricultural and Biological Sciences 6 17%
Computer Science 6 17%
Medicine and Dentistry 2 6%
Mathematics 1 3%
Other 3 9%
Unknown 9 26%
Attention Score in Context

Attention Score in Context

This research output has an Altmetric Attention Score of 5. 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 04 January 2024.
All research outputs
#6,820,116
of 25,099,766 outputs
Outputs from BMC Genomics
#2,704
of 11,156 outputs
Outputs of similar age
#100,436
of 314,732 outputs
Outputs of similar age from BMC Genomics
#51
of 188 outputs
Altmetric has tracked 25,099,766 research outputs across all sources so far. This one has received more attention than most of these and is in the 72nd percentile.
So far Altmetric has tracked 11,156 research outputs from this source. They receive a mean Attention Score of 4.8. This one has done well, scoring higher than 75% of its peers.
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 314,732 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 67% of its contemporaries.
We're also able to compare this research output to 188 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 72% of its contemporaries.