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SRX2408917: GSM2420675: HEK293T_clone1_SC_average_6; Homo sapiens; RNA-Seq
1 ILLUMINA (NextSeq 500) run: 7.4M spots, 1.2G bases, 444Mb downloads

Submitted by: NCBI (GEO)
Study: Effective Detection of Variation in Single Cell Transcriptome using MATQ-seq
show Abstracthide Abstract
We report here a new single-cell RNA-seq assay, Multiple Annealing and dC-Tailing based Quantitative single-cell RNA-seq (MATQ-seq), which provides the accuracy and sensitivity that enable the detection of transcriptional variations existing in single cells of the same type. We performed a systematic characterization of the technical noise using pool-and-split averaged single-cell samples and showed that the biological variations in single cells were observed with statistical significance. Overall design: 10 HEK293T single cells and 10 HEK293T pool-and-split averaged single cell samples were sequenced with MATQ-seq. We also sequenced 6 MCF10A single cells and 6MCF10A pool-and-split averaged single cell samples. To characterize the capture efficiency, we also sequenced 6 averaged one-fifth MCF10A single-cell samples with ERCC spike-in. Additional 38 HEK293T single cells (HEK293T_clone1_SC*) and 10 HEK293T pool-and-split averaged single cell samples (HEK293T_clone1_SC_average*) were sequenced with MATQ-seq.
Sample: HEK293T_clone1_SC_average_6
SAMN06127895 • SRS1847222 • All experiments • All runs
Organism: Homo sapiens
Library:
Instrument: NextSeq 500
Strategy: RNA-Seq
Source: TRANSCRIPTOMIC
Selection: cDNA
Layout: PAIRED
Construction protocol: cDNA libraries were prepared for sequencing using standard Illumina Truseq protocols
Experiment attributes:
GEO Accession: GSM2420675
Links:
Runs: 1 run, 7.4M spots, 1.2G bases, 444Mb
Run# of Spots# of BasesSizePublished
SRR50920067,427,3171.2G444Mb2017-01-03

ID:
3500946

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