W
W. Evan Johnson
Researcher at Boston University
Publications - 85
Citations - 16203
W. Evan Johnson is an academic researcher from Boston University. The author has contributed to research in topics: RNA & Gene. The author has an hindex of 31, co-authored 84 publications receiving 12033 citations. Previous affiliations of W. Evan Johnson include Harvard University & University of Utah.
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Journal ArticleDOI
Adjusting batch effects in microarray expression data using empirical Bayes methods
TL;DR: This paper proposed parametric and non-parametric empirical Bayes frameworks for adjusting data for batch effects that is robust to outliers in small sample sizes and performs comparable to existing methods for large samples.
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The sva package for removing batch effects and other unwanted variation in high-throughput experiments
TL;DR: The sva package is described, which supports surrogate variable estimation with the sva function, direct adjustment for known batch effects with the ComBat function and adjustment for batch and latent variables in prediction problems with the fsva function.
Journal ArticleDOI
Tackling the widespread and critical impact of batch effects in high-throughput data
Jeffrey T. Leek,Robert B. Scharpf,Héctor Corrada Bravo,Héctor Corrada Bravo,David M. Simcha,Benjamin Langmead,W. Evan Johnson,Donald Geman,Keith A. Baggerly,Rafael A. Irizarry +9 more
TL;DR: It is argued that batch effects (as well as other technical and biological artefacts) are widespread and critical to address and experimental and computational approaches for doing so are reviewed.
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Low concordance of multiple variant-calling pipelines: practical implications for exome and genome sequencing
Jason O'Rawe,Jason O'Rawe,Tao Jiang,Guangqing Sun,Yiyang Wu,Yiyang Wu,Wei Min Wang,Jingchu Hu,Paul Bodily,Lifeng Tian,Hakon Hakonarson,W. Evan Johnson,Zhi Wei,Kai Wang,Kai Wang,Gholson J. Lyon,Gholson J. Lyon,Gholson J. Lyon +17 more
TL;DR: The results suggest that more caution should be exercised in genomic medicine settings when analyzing individual genomes, including interpreting positive and negative findings with scrutiny, especially for indels.
Journal ArticleDOI
Model-based analysis of tiling-arrays for ChIP-chip
W. Evan Johnson,Wei Li,Clifford A. Meyer,Raphael Gottardo,Jason S. Carroll,Myles Brown,X. Shirley Liu +6 more
TL;DR: A fast and powerful analysis algorithm to reliably detect regions enriched by transcription factor chromatin immunoprecipitation on Affymetrix tiling arrays (ChIP-chip), developed in open-source Python and available at http://chip.dfci.harvard.edu/∼wli/MAT.