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FastDMA: An Infinium HumanMethylation450 Beadchip Analyzer

Overview of attention for article published in PLOS ONE, September 2013
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Title
FastDMA: An Infinium HumanMethylation450 Beadchip Analyzer
Published in
PLOS ONE, September 2013
DOI 10.1371/journal.pone.0074275
Pubmed ID
Authors

Dingming Wu, Jin Gu, Michael Q. Zhang

Abstract

DNA methylation is vital for many essential biological processes and human diseases. Illumina Infinium HumanMethylation450 Beadchip is a recently developed platform studying genome-wide DNA methylation state on more than 480,000 CpG sites and a few CHG sites with high data quality. To analyze the data of this promising platform, we developed FastDMA which can be used to identify significantly differentially methylated probes. Besides single probe analysis, FastDMA can also do region-based analysis for identifying the differentially methylated region (DMRs). A uniformed statistical model, analysis of covariance (ANCOVA), is used to achieve all the analyses in FastDMA. We apply FastDMA on three large-scale DNA methylation datasets from The Cancer Genome Atlas (TCGA) and find many differentially methylated genomic sites in different types of cancer. On the testing datasets, FastDMA shows much higher computational efficiency than current tools. FastDMA can benefit the data analyses of large-scale DNA methylation studies with an integrative pipeline and a high computational efficiency. The software is freely available via http://bioinfo.au.tsinghua.edu.cn/software/fastdma/.

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Geographical breakdown

Country Count As %
United States 1 2%
Turkey 1 2%
Unknown 41 95%

Demographic breakdown

Readers by professional status Count As %
Student > Ph. D. Student 9 21%
Researcher 5 12%
Professor > Associate Professor 5 12%
Student > Master 5 12%
Student > Bachelor 4 9%
Other 12 28%
Unknown 3 7%
Readers by discipline Count As %
Agricultural and Biological Sciences 11 26%
Biochemistry, Genetics and Molecular Biology 9 21%
Computer Science 6 14%
Medicine and Dentistry 5 12%
Engineering 4 9%
Other 2 5%
Unknown 6 14%