End Sequence Analysis Toolkit (ESAT) expands the extractable information from single-cell RNA-seq data

• DOI: 10.1101/gr.207902.116
• Publication Date: 2016-07-29T02:28:31Z
• Authors: Alan Derr; Chaoxing Yang; Rapolas Zilionis; Alexey Sergushichev; David M. Blodgett; Sambra Redick; Rita Bortell; Jeremy Luban; David M. Harlan; Sebastian Kadener; Dale L. Greiner; Allon Klein; Maxim N. Artyomov; Manuel Garber
• Keywords: RNA-Seq; ESAT-6

RNA-seq protocols that focus on transcript termini are well suited for applications in which template quantity is limiting. Here we show that, when applied to end-sequencing data, analytical methods designed global produce computational artifacts. To remedy this, created the End Sequence Analysis Toolkit (ESAT). As a test, first compared and bulk using RNA from dendritic cells stimulated with lipopolysaccharide (LPS). predicted by telescripting model transcriptional bursts, ESAT detected an LPS-stimulated shift shorter 3′-isoforms was not evident conventional methods. Then, droplet-based microfluidics used generate 1000 cDNA libraries, each individual pancreatic islet cell. identified nine distinct cell types, three β-cell complex interplay between hormone secretion vascularization. ESAT, then, offers much-needed generally applicable pipeline either or single-cell end-sequencing.