Ontology highlight
ABSTRACT: Unlabelled
A major roadblock towards accurate interpretation of single cell RNA-seq data is large technical noise resulted from small amount of input materials. The existing methods mainly aim to find differentially expressed genes rather than directly de-noise the single cell data. We present here a powerful but simple method to remove technical noise and explicitly compute the true gene expression levels based on spike-in ERCC molecules.Availability and implementation
The software is implemented by R and the download version is available at http://wanglab.ucsd.edu/star/GRM.Contact
wei-wang@ucsd.eduSupplementary information
Supplementary data are available at Bioinformatics online.
SUBMITTER: Ding B
PROVIDER: S-EPMC4481848 | biostudies-literature | 2015 Jul
REPOSITORIES: biostudies-literature
Ding Bo B Zheng Lina L Zhu Yun Y Li Nan N Jia Haiyang H Ai Rizi R Wildberg Andre A Wang Wei W
Bioinformatics (Oxford, England) 20150224 13
<h4>Unlabelled</h4>A major roadblock towards accurate interpretation of single cell RNA-seq data is large technical noise resulted from small amount of input materials. The existing methods mainly aim to find differentially expressed genes rather than directly de-noise the single cell data. We present here a powerful but simple method to remove technical noise and explicitly compute the true gene expression levels based on spike-in ERCC molecules.<h4>Availability and implementation</h4>The softw ...[more]