Transcriptome-based Phenotyping Project

This project is developing a general approach for characterizing and classifying cells according to transcriptome profiles from RNAseq data. This approach will be applicable to classifying samples according to cell type, tissue of origin, developmental stage, disease state, and active cellular processes.

Related CPCP Publications

OEFinder: a user interface to identify and visualize ordering effects in single-cell RNA-seq data. Leng N, Choi J, Chu LF, Thomson JA, Kendziorski C, Stewart R. Bioinformatics 32(9):1408-10, 2016

Publication details

Hematopoietic signaling mechanism revealed from a stem/progenitor cell cistrome. Hewitt KJ, Kim DH, Devadas P, Prathibha R, Zuo C, Sanalkumar R, Johnson D, Kang Y-A, Kim J-S, Dewey CN, Keles S, Bresnick EH. Molecular Cell 9(1):62–74, 2015

Publication details

EBSeq-HMM: A Bayesian approach for identifying gene-expression changes in ordered RNA-seq experiments. Leng N, Li Y, McIntosh BE, Nguyen BK, Duffin B, Tian S, Thomson JA, Dewey C, Stewart R, Kendziorski C. Bioinformatics 31(16):2614-2622, 2015

Publication details

Lead

Colin Dewey

Investigators

Christina Kendziorski

Nate Fillmore

Rhonda Bacher

Resources

MetaSRA pipeline software

MetaSRA: normalized metadata for the Sequence Read Archive data

CPCP Retreat 2016: Entity Matching for EHR- and Transcriptome-based Phenotyping Symposium Video

OEFinder software

Oscope software

EBSeqHMM software