Normalization and noise reduction for single cell RNA-seq experiments.
basic_science · Level V
Where this comes from
- Record sourced from PubMed, PMID 25717193.
- Also identified by DOI 10.1093/bioinformatics/btv122 and PMC identifier 4481848.
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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.edu Supplementary data are available at Bioinformatics online.
Medical subject headings
- Gene Expression Profiling
- High-Throughput Nucleotide Sequencing
- Sequence Analysis, RNA
- Single-Cell Analysis
- Software