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Series GSE54006 Query DataSets for GSE54006
Status Public on Feb 14, 2014
Title Massively parallel single-cell RNA-Seq for dissecting cell type and cell state compositions
Organism Mus musculus
Experiment type Expression profiling by high throughput sequencing
Summary In multi-cellular organisms, biological function emerges when cells of heterogeneous types and states are combined into complex tissues. Nevertheless unbiased dissection of tissues into coherent cell subpopulations is currently lacking. We introduce an automated, massively parallel single cell RNA sequencing method for intuitively analyzing in-vivo transcriptional states in thousands of single cells. Combined with unsupervised classification algorithms, it facilitates ab initio and marker-free characterization of classical hematopoietic cell types from splenic tissues. Importantly, modeling single cells transcriptional states in dendritic cells subpopulations, where a cell type hierarchy is difficult to define with marker-based approaches, uncovers complex combinatorial activity of multiple gene modules and capture cell-to-cell variability in steady state conditions and following pathogen activation. Massively parallel single cell RNA-seq thereby emerges as an effective tool for unbiased dissection of complex tissues.
 
Overall design CD11c+ enriched splenocyte mRNA profiles from single cells were generated by deep sequencing of thousands of single cells, sequenced in several batches in an Illumina Hiseq 2000

The 'umitab.txt' processed data file contains the mRNA counts (post-filtering RMT counts) of a gene per each well (columns)
The 'experimental_design.txt' contains a detailed information regarding each well.
The 'readme0421.txt' was provided with details about each supplementary file.
 
Contributor(s) Amit I, Tanay A, Jaitin D, Kenigsberg E, Keren-Shaul H
Citation(s) 24531970
Submission date Jan 12, 2014
Last update date Mar 19, 2019
Contact name Ido Amit
E-mail ido.amit@weizmann.ac.il
Phone 972-8-9343338
Organization name Weizmann Institute of Science
Department Immunology
Street address 234 Herzl st.
City Rehovot
ZIP/Postal code 760001
Country Israel
 
Platforms (1)
GPL13112 Illumina HiSeq 2000 (Mus musculus)
Samples (28)
GSM1305777 Sample 1_batch 0
GSM1305778 Sample 2_batch 1
GSM1305779 Sample 3_batch 2
Relations
BioProject PRJNA234330
SRA SRP035326

Download family Format
SOFT formatted family file(s) SOFTHelp
MINiML formatted family file(s) MINiMLHelp
Series Matrix File(s) TXTHelp

Supplementary file Size Download File type/resource
GSE54006_experimental_design.txt.gz 51.0 Kb (ftp)(http) TXT
GSE54006_readme0421.txt 651 b (ftp)(http) TXT
GSE54006_umitab.txt.gz 3.9 Mb (ftp)(http) TXT
Raw data are available in SRA
Processed data is available on Series record

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