Transcriptomics

Dataset Information

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Quantitative single-cell RNA-seq


ABSTRACT: Purpose: We applied cDNA molecule counting using unique molecular identifiers combined with high-throughput sequencing to study the transcriptome of individual mouse embryonic stem cells, with spike-in controls to monitor technical performance. We further examined transcriptional noise in the embryonic stem cells. One 96-well plate of single-stranded cDNA libraries generated from 96 single R1 mouse embryonic stem cells sequenced on two lanes, and one 96-well plate of the same libraries further amplified by 9 PCR cycles sequenced on one lane.

ORGANISM(S): Mus musculus  

SUBMITTER: Pawel Zajac  Sten Linnarsson   Saiful Islam   Peter Lönnerberg   Amit Zeisel   Gioele La Manno   Simon Joost    

PROVIDER: E-GEOD-46980 | ArrayExpress | 2013-12-20

SECONDARY ACCESSION(S): SRP022764GSE46980PRJNA203208

REPOSITORIES: GEO, ArrayExpress, ENA

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Publications

Quantitative single-cell RNA-seq with unique molecular identifiers.

Islam Saiful S   Zeisel Amit A   Joost Simon S   La Manno Gioele G   Zajac Pawel P   Kasper Maria M   Lönnerberg Peter P   Linnarsson Sten S  

Nature methods 20131222 2


Single-cell RNA sequencing (RNA-seq) is a powerful tool to reveal cellular heterogeneity, discover new cell types and characterize tumor microevolution. However, losses in cDNA synthesis and bias in cDNA amplification lead to severe quantitative errors. We show that molecular labels--random sequences that label individual molecules--can nearly eliminate amplification noise, and that microfluidic sample preparation and optimized reagents produce a fivefold improvement in mRNA capture efficiency. ...[more]

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