Modeling of RNA-seq fragment sequence bias reduces systematic errors in transcript abundance estimation

September 29, 2016 Leave a comment 4,232 Views

Current computational methods for estimating transcript abundance from RNA-seq data can lead to hundreds of false-positive results. Researchers from the Dana-Farber Cancer Institute show that these systematic errors stem largely from a failure to model fragment GC content bias. Sample-specific ...

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Modeling of RNA-seq fragment sequence bias reduces systematic errors in transcript abundance estimation

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