Single-Cell Transcriptomics Bioinformatics and Computational Challenges-Reference-Cited by-同舟云学术

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Single-Cell Transcriptomics Bioinformatics and Computational Challenges

Published:2016-09-21 Issue: Volume:7 Page:
ISSN:1664-8021
Container-title:Frontiers in Genetics
language:
Short-container-title:Front. Genet.

Author:

Poirion Olivier B.,Zhu Xun,Ching Travers,Garmire Lana

Funder

National Institute of Environmental Health Sciences

National Institute of General Medical Sciences

Hawaii Community Foundation

U.S. National Library of Medicine

Publisher

Frontiers Media SA

Subject

Genetics(clinical),Genetics,Molecular Medicine

Reference110 articles.

1. Pooling across cells to normalize single-cell RNA sequencing data with many zero counts;Aaron;Genome Biol.,2016

2. viSNE enables visualization of high dimensional single-cell data and reveals phenotypic heterogeneity of leukemia;Amir;Nat. Biotechnol.,2013

3. Differential expression analysis for sequence count data;Anders;Genome Biol.,2010

4. HTSeq—a python framework to work with high-throughput sequencing data;Anders;Bioinformatics,2014

5. FastQC: a quality control tool for high throughput sequence data;Andrews,2010

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