End Sequence Analysis ToolKit ( ESAT ) expands the extractable from single cell RNA-seq experiments
semanticscholar(2016)
摘要
RNAseq protocols that focus on transcript termini are wellsuited for applications in which template quantity is limiting. Here we show that, when applied to endsequencing data, analytical methods designed for global RNAseq produce computational artifacts. To remedy this we created the End Sequence Analysis Toolkit (ESAT). As a test, we first compared endsequencing and bulk RNAseq using RNA from dendritic cells stimulated with lipopolysaccharide (LPS). As predicted by the telescripting model for transcriptional bursts, ESAT detected an LPSstimulated shift to shorter 3’isoforms that was not evident by conventional computational methods. Then, dropletbased microfluidics was used to generate 1,000 cDNA libraries, each from an individual pancreatic islet cell. ESAT identified 9 distinct cell types, three distinct βcell types, and a complex interplay between hormone secretion and vascularization. ESAT, then, offers a muchneeded and generally applicable computational pipeline for either bulk or single cell RNA endsequencing. Cold Spring Harbor Laboratory Press on August 10, 2016 Published by genome.cshlp.org Downloaded from
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