Expression and Quantification

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Comparing Data Across RNA-Seq Studies

Comparing Data Across RNA-Seq Studies

High-throughput sequencing is now regularly used for studies of the transcriptome (RNA-seq), particularly for comparisons among experimental conditions. For the time being, a limited number of biological replicates are typically considered in such experiments, leading to low detection power for ...

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Fixseq – Universal count correction for high-throughput sequencing

Fixseq – Universal count correction for high-throughput sequencing

Researchers at MIT show that existing RNA-seq, DNase-seq, and ChIP-seq data exhibit overdispersed per-base read count distributions that are not matched to existing computational method assumptions. To compensate for this overdispersion we introduce a nonparametric and universal method for processing ...

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Optimal Bayesian Classification Tutorial

Optimal Bayesian Classification Tutorial

An overview of the SAMCNet package (available at https://github.com/binarybana/samcnet) that implements optimal Bayesian classification for RNA-Seq data as part of an upcoming publication. (Publication details will follow once reviewed and accepted)

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TRAP – Time-series RNA-seq Analysis Package

TRAP – Time-series RNA-seq Analysis Package

Measuring expression levels of genes at the whole genome level can be useful for many purposes, especially for revealing biological pathways underlying specific phenotype conditions. When gene expression is measured over a time period, we have opportunities to understand how ...

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