github link
Accession IconSRP071245

Effective Detection of Variation in Single Cell Transcriptome using MATQ-seq

Organism Icon Homo sapiens
Sample Icon No Downloadable Samples
Technology Badge IconNextSeq 500

Submitter Supplied Information

Description
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.
PubMed ID
Total Samples
91
Submitter’s Institution
No associated institution
Alternate Accession IDs

Samples

Show of 0 Total Samples
Filter
Add/Remove
Accession Code
Title
Processing Information
Additional Metadata
No rows found
Loading...