Author

Stephane E Castel

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· 1 Genetics· 1 Genomics· 1

Signature Assays, Organisms & Methods

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Assay:bulk RNA-seq· 3 Approach:statistical model· 3 Research Focus:variant calling· 2 Research Focus:differential expression· 1 Research Focus:eQTL / molecular QTL mapping· 1 Research Focus:gene regulatory network inference· 1 Organism:human· 1

Frequent Co-Authors

Pejman MohammadiiD· 3 shared Tuuli LappalaineniD· 3 shared Ami Levy-Moonshine· 1 shared Andrew A Brown· 1 shared Eric Banks· 1 shared Wendy K Chung· 1 shared Yufeng Shen· 1 shared

Activity by Year

2015-2017 · peak 1/yr

Co-Author Collaboration Network

7 top collaborators · 13 mutual co-author links

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3 shared papersBioinformatics

Pejman MohammadiORCID

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3 papers

Recent·Most cited

Quantifying the regulatory effect size of cis-acting genetic variation using allelic fold change

Pejman Mohammadi, Stephane E Castel, Andrew A Brown, Tuuli Lappalainen

This paper introduces log allelic fold change (aFC) as a measure for quantifying cis-eQTL effect sizes, showing its consistency across datasets and independence from expression level and allele frequency.

Genome Research · Oct 11, 2017Peer-reviewedBioinformatics

Rare variant phasing and haplotypic expression from RNA-sequencing with phASER

Stephane E Castel, Pejman Mohammadi, Wendy K Chung, Yufeng Shen, Tuuli Lappalainen

This paper introduces phASER, a method for phasing variants from RNA-seq data, improving accuracy for rare and de novo variants and enabling haplotypic expression analysis.

bioRxiv · Jun 3, 2016Genetics

Tools and best practices for allelic expression analysis

Stephane E Castel, Ami Levy-Moonshine, Pejman Mohammadi, Eric Banks, Tuuli Lappalainen

This paper analyzes allelic expression read count data, identifies technical errors, and introduces software for high-throughput AE analysis to improve data quality.

bioRxiv · Mar 6, 2015Genomics