Author

Mark D Robinson

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· 5

Signature Assays, Organisms & Methods

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Approach:statistical model· 4 Research Focus:differential expression· 3 Approach:benchmark study· 2 Assay:bulk RNA-seq· 2 Research Focus:variant effect prediction· 2 Approach:Bayesian inference· 1 Research Focus:benchmarking· 1 Assay:DNA methylation· 1

Frequent Co-Authors

Charity W Law· 2 shared Charlotte Soneson· 2 shared Helen Lindsay· 2 shared Malgorzata Nowicka· 2 shared Xiaobei Zhou· 2 shared Abdullah Kahraman· 1 shared Alexa BurgeriD· 1 shared Anastasia FelkeriD· 1 shared

Activity by Year

2014-2016 · peak 3/yr

Co-Author Collaboration Network

10 top collaborators · 22 mutual co-author links

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2 shared papersBioinformatics

Charity W Law

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5 papers

Recent·Most cited

CrispRVariants: precisely charting the mutation spectrum in genome engineering experiments

Helen Lindsay, Alexa Burger, Berthin Biyong, Anastasia Felker, Christopher Hess, Jonas Zaugg, Elena Chiavacci, Carolin Anders, Martin Jinek, Christian Mosimann, Mark D Robinson

CrispRVariants provides a toolkit to accurately assess mutagenesis efficiency in genome editing experiments by analyzing sequencing data and resolving mutant alleles.

bioRxiv · Mar 10, 2016Bioinformatics

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

iCOBRA: open, reproducible, standardized and live method benchmarking

Charlotte Soneson, Mark D Robinson

iCOBRA provides a web-based tool and R package for benchmarking and comparing method performance with ground truth, enabling reproducible and standardized evaluations.

bioRxiv · Dec 1, 2015Bioinformatics

Differential transcript usage from RNA-seq data: isoform pre-filtering improves performance of count-based methods

Charlotte Soneson, Katarina L Matthes, Malgorzata Nowicka, Charity W Law, Mark D Robinson

The paper evaluates methods for detecting differential transcript usage from RNA-seq data, showing that isoform-level pre-filtering improves false discovery rate control.

bioRxiv · Oct 13, 2015Bioinformatics

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