Author

Xiaobei Zhou

Listed by name: these papers carry no ORCID for this author, so different people with the same name may be mixed together.

Biology Disciplines

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Bioinformatics· 3

Signature Assays, Organisms & Methods

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Approach:statistical model· 3 Research Focus:differential expression· 2 Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Assay:bulk RNA-seq· 1 Assay:DNA methylation· 1 Research Focus:variant effect prediction· 1

Frequent Co-Authors

Mark D Robinson· 2 shared Abdullah Kahraman· 1 shared Charity W Law· 1 shared Charity W. Law· 1 shared Helen Lindsay· 1 shared Lukas M Weber· 1 shared Malgorzata Nowicka· 1 shared Mark D. RobinsoniD· 1 shared

Activity by Year

2014-2015 · peak 2/yr

Co-Author Collaboration Network

8 top collaborators · 16 mutual co-author links

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2 shared papersBioinformatics

Mark D Robinson

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3 papers

Recent·Most cited

Do count-based differential expression methods perform poorly when genes are expressed in only one condition?

Xiaobei Zhou, Mark D Robinson

The paper evaluates differential gene expression methods for RNA-seq data and finds that count-based methods may not perform poorly when genes are expressed in only one condition.

Genome Biology · Dec 1, 2015Peer-reviewedBioinformatics

benchmarkR: an R package for benchmarking genome-scale methods

Xiaobei Zhou, Charity W. Law, Mark D. Robinson

benchmarkR evaluates and visualizes statistical methods' performance on genomic datasets with known truth, focusing on FDR control and calibration.

bioRxiv · Apr 17, 2015 · PreprintBioinformatics

MINI REVIEW: Statistical methods for detecting differentially methylated loci and regions

Mark D Robinson, Abdullah Kahraman, Charity W Law, Helen Lindsay, Malgorzata Nowicka, Lukas M Weber, Xiaobei Zhou

This paper reviews statistical methods for detecting differentially methylated loci and regions, focusing on challenges like experimental design, false discovery control, and batch effects.

Frontiers in Genetics · Sep 16, 2014Peer-reviewedBioinformatics