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Results for: Publications | Transcriptome-based Phenotyping Project

IPI59: An actionable biomarker to improve treatment response in serous ovarian carcinoma patients. Choi J, Ye S, Eng K, Korthauer K, Bradley W, Rader J, Kendziorski C. Statistics in Biosciences 9(1):1-12, 2017.

Analysis of embryonic development in the unsequenced axolotl: waves of transcriptional upheaval and stability. Jiang P, Nelson J, Leng N, Collins M, Swanson S, Dewey C, Thomson J, Stewart R. Developmental Biology 426(2):143-154, 2017.

Statistical methods for latent class quantitative trait loci mapping. Ye S, Bacher R, Keller MP, Attie AD, Kendziorski C. Genetics 206(3):1309-1317, 2017.

MetaSRA: normalized human sample-specific metadata for the Sequence Read Archive. Bernstein M, Doan A, Dewey C. Bioinformatics 33(18):2914–2923, 2017.

SCnorm: robust normalization of single-cell RNA-seq data. Bacher R, Chu LF, Leng N, Gasch A, Thomson J, Stewart R, Newton M, Kendziorski C. Nature Methods 14:584–586, 2017.

A statistical approach for identifying differential distributions in single-cell RNA-seq experiments. Korthauer K, Chu LF, Newton M, Li Y, Thomson J, Stewart R, Kendziorski K. Genome Biology 17:222, 2016.

Single-cell RNA-seq reveals novel regulators of human embryonic stem cell differentiation to definitive endoderm. Chu LF, Leng N, Zhang J, Hou Z, Mamott D, Vereide D, Choi J, Kendziorski C, Stewart R, Thomson J. Genome Biology 17:173, 2016.

Integrative analysis with ChIP-seq advances the limits of transcript quantification from RNA-seq. Liu P, Sanalkumar R, Bresnick E, Keles S, Dewey C. Genome Research 26:1124–1133, 2016.

Design and computational analysis of single-cell RNA-sequencing experiments. Bacher R, Kendziorski C. Genome Biology 17:173, 2016.

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.

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