Expression and Quantification

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Parametric analysis of RNA-seq expression data

Parametric analysis of RNA-seq expression data

Various methods had been introduced for normalization and comparison of RNA-seq count data. However, they lacked objectivity because they based on ad hoc assumptions that were never verified their appropriateness. Here, researchers from Akita Prefectural University introduced a method that assumes ...

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Flexible expressed region analysis for RNA-seq with derfinder

Flexible expressed region analysis for RNA-seq with derfinder

Differential expression analysis of RNA sequencing (RNA-seq) data typically relies on reconstructing transcripts or counting reads that overlap known gene structures. Researchers at Johns Hopkins University previously introduced an intermediate statistical approach called differentially expressed region (DER) finder that seeks ...

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kallisto – Near-optimal probabilistic RNA-seq quantification

kallisto – Near-optimal probabilistic RNA-seq quantification

Researchers from the University of California, Berkeley  and the University of Iceland have developed kallisto, an RNA-seq quantification program that is two orders of magnitude faster than previous approaches and achieves similar accuracy. Kallisto pseudoaligns reads to a reference, producing ...

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