Predict A to I editing from a single RNA-seq data set of modest sequencing depth

March 5, 2015 Leave a comment 4,817 Views

UCLA life scientists have created an accurate new method to identify genetic markers for many diseases — a significant step toward a new era of personalized medicine, tailored to each person’s DNA and RNA. The powerful method, called GIREMI (pronounced ...

RNA-Seq Blog Transcriptome Research & Industry News

Tag Archives: sequence-independent

Predict A to I editing from a single RNA-seq data set of modest sequencing depth

dsRID – in silico identification of dsRNA regions using long-read RNA-seq data

FUN-PROSE – predicting the response of fungal genes

Unraveling the timeline of gene expression – a pseudotemporal trajectory analysis of single-cell RNA sequencing data

INVADEseq – cataloging bacterial diversity within tumor samples

RNA sequencing identifies genetic effects of traumatic brain injury using an artificial brain

Researchers develop new method to identify and remove background noise from single cell data

scReadSim – a single-cell RNA-seq and ATAC-seq read simulator