TitleMassive and parallel expression profiling using microarrayed single-cell sequencing
Data descriptionSingle-cell RNA-seq of human melanoma tumor cells
Doi10.1038/ncomms13182
Web-link of the paperhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4944528
Data typescRNA-seq
DatabaseSRA
Accession numberSRP067878
URL of the datahttp://www.spatialtranscriptomicsresearch.org/datasets/doi10-1038ncomms13182/
SpeciesHuman
TissueBreast
Blood
Cell typeMCF-7
B cells
Number of cells136
1189
Cell capture platformFACS
Library preparation protocolMASC-seq
Unique molecular identifier (Y/N)Y
Spike-in (Y/N)N
Full-length (Y/N)N
Brief summary of the scientific questionThey present a method enabling massive microarray-based barcoding of expression patterns in single cells, termed MASC-seq. This technology enables both imaging and high-throughput single-cell analysis, characterizing thousands of single-cell transcriptomes per day at a low cost.
Brief summary of the bioinformatics processingExpression analysis of single MCF-7 cells by hierarchical clustering of Pearson’s correlation distances, and t-SNE;
Barcode cross-walk evaluation;
Expression analysis of CLL single cells;
Cell-cycle analysis.
CitationVickovic, S., Stahl, P. L., Salmen, F., Giatrellis, S., Westholm, J. O., Mollbrink, A., . . . Lundeberg, J. (2016). Massive and parallel expression profiling using microarrayed single-cell sequencing. Nat Commun, 7, 13182. doi:10.1038/ncomms13182
Web-link of the paperhttps://www.ncbi.nlm.nih.gov/pmc/articles/PMC4944528