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Normalization and noise reduction for single cell RNA-seq experiments.

ABSTRACT: 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.The software is implemented by R and the download version is available at http://wanglab.ucsd.edu/star/GRM.wei-wang@ucsd.eduSupplementary data are available at Bioinformatics online.

SUBMITTER: Ding B 

PROVIDER: S-EPMC4481848 | biostudies-literature | 2015 Jul

REPOSITORIES: biostudies-literature

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Normalization and noise reduction for single cell RNA-seq experiments.

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]

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