Dataset Information


Single cell profiling of mouse blood cells using CEL-seq2

ABSTRACT: Gene expression in mouse blood cells from sorted via FACS analysis into a 384-well plate were profiled using a modified CEL-seq2 protocol. Overall design: B lymphocytes (B220+ FSC-Alow), erythroblasts (Ter119+ CD44+, FSC-Amid/high), granulocytes (Mac1+ Gr1+) and high-end progenitor/stem (Lin- Kit+ Sca1+) were sorted from the bone marrow of a C57BL/6 10-13 week old female. T cells (CD3+ FSC-Alow) were isolated from the thymus of the same mouse. Bone marrow and thymus were dissociated mechanically, washed and stained with antibodies for 1hr on ice. Single cells were deposited on a 384 well plate using an Aria cell sorter (Beckman). Index data was collected and an adapted CEL-seq2 protocol used to generate a library for sequencing. The reads were sequenced by Illumina Nextseq and preprocessed by the scPipe R/Bioconductor software.

INSTRUMENT(S): Illumina NextSeq 500 (Mus musculus)


PROVIDER: GSE109999 | GEO | 2018-02-28


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scPipe: A flexible R/Bioconductor preprocessing pipeline for single-cell RNA-sequencing data.

Tian Luyi L   Su Shian S   Dong Xueyi X   Amann-Zalcenstein Daniela D   Biben Christine C   Seidi Azadeh A   Hilton Douglas J DJ   Naik Shalin H SH   Ritchie Matthew E ME  

PLoS computational biology 20180810 8

Single-cell RNA sequencing (scRNA-seq) technology allows researchers to profile the transcriptomes of thousands of cells simultaneously. Protocols that incorporate both designed and random barcodes have greatly increased the throughput of scRNA-seq, but give rise to a more complex data structure. There is a need for new tools that can handle the various barcoding strategies used by different protocols and exploit this information for quality assessment at the sample-level and provide effective v  ...[more]

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