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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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SCell – integrated analysis of single-cell RNA-seq data

SCell – integrated analysis of single-cell RNA-seq data

Analysis of the composition of heterogeneous tissue has been greatly enabled by recent developments in single-cell transcriptomics. Researchers from UCSF have developed SCell, an integrated software tool for quality filtering, normalization, feature selection, iterative dimensionality reduction, clustering and the estimation ...

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Improved definition of the mouse transcriptome via targeted RNA sequencing

Improved definition of the mouse transcriptome via targeted RNA sequencing

Targeted RNA sequencing (CaptureSeq) uses oligonucleotide probes to capture RNAs for sequencing, providing enriched read coverage, accurate measurement of gene expression, and quantitative expression data. Researchers from the European Bioinformatics Institute applied CaptureSeq to refine transcript annotations in the current ...

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Optimizing RNA-Seq Mapping with STAR

Optimizing RNA-Seq Mapping with STAR

Sequencing of transcribed RNA molecules (RNA-seq) is an invaluable tool for studying cell transcriptomes at high resolution and depth. RNA-seq datasets typically consist of tens to hundreds of millions of relatively short (30–200 nt) sequence fragments of the original RNA ...

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