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Series GSE62050 Query DataSets for GSE62050
Status Public on Jun 05, 2015
Title High-Throughput Single-Cell Labeling (Hi-SCL) for RNA-Seq using drop-based microfluidics
Organism Mus musculus
Experiment type Expression profiling by high throughput sequencing
Summary The importance of single-cell level data is increasingly appreciated, and significant advances in this direction have been made in recent years. Common to these technologies is the need to physically segregate individual cells into containers, such as wells or chambers of a micro-fluidics chip. High-throughput Single-Cell Labeling (Hi-SCL) in drops is a novel method that uses drop-based libraries of oligonucleotide barcodes to index individual cells in a population. The use of drops as containers, and a microfluidics platform to manipulate them en-masse, yields a highly scalable methodological framework. Once tagged, labeled molecules from different cells may be mixed without losing the cell-of-origin information. Here we demonstrate an application of the method for generating RNA-sequencing data for multiple individual cells within a population. Barcoded oligonucleotides are used to prime cDNA synthesis within drops. Barcoded cDNAs are then combined and subjected to second generation sequencing. The data are deconvoluted based on the barcodes, yielding single-cell mRNA expression data. In a proof-of-concept set of experiments we show that this method yields data comparable to other existing methods, but with unique potential for assaying very large numbers of cells.
Overall design In this experiment we mixed 2 cell types (mES mEF) and then using single cell novel approach we could be able to find each cell (using its barcode) and assign it to mES of mEF and to produce mES and mEF aggregate bam files (converted to bed for GEO submission).
1152_RNA_RTprimers_Barcodes.txt: A list of all 1152 barcodes sequenced for Read2 fastq files.
Contributor(s) Rotem A, Ram O, Shoresh N
Citation(s) 26000628
Submission date Oct 03, 2014
Last update date May 15, 2019
Contact name oren ram
Phone 6178343661
Organization name Broad institute
Department epigenomics
Lab Brad Bernstein
Street address 415 Main Street
City cambridge
State/province MASSACHUSETTS
ZIP/Postal code 02142
Country USA
Platforms (1)
GPL16417 Illumina MiSeq (Mus musculus)
Samples (6)
GSM1518962 tagged-375_S2
GSM1518963 tagged-630_S3
GSM1518964 tagged-726_S1
BioProject PRJNA263039
SRA SRP048628

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Supplementary file Size Download File type/resource
GSE62050_1152_RNA_RTprimers_Barcodes.txt.gz 7.5 Kb (ftp)(http) TXT
GSE62050_mEF.sorted.bed.gz 4.2 Mb (ftp)(http) BED
GSE62050_mES.sorted.bed.gz 6.9 Mb (ftp)(http) BED
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Raw data are available in SRA
Processed data are available on Series record

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