Detecting and quantifying isoforms from RNA-seq data is an important but challenging task. The problem is often ill-posed, particularly at low coverage. One promising direction is to exploit several samples simultaneously. A team led by researchers at MINES ParisTech have ...
Read More »FlipFlop – Efficient RNA Isoform Identification and Quantification from RNA-Seq Data with Network Flows
Several state-of-the-art methods for isoform identification and quantification are based on l1-regularized regression, such as the Lasso. However, explicitly listing the-possibly exponentially-large set of candidate transcripts is intractable for genes with many exons. For this reason, existing approaches using the ...
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