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Sample GSM1597746 Query DataSets for GSM1597746
Status Public on Jun 17, 2015
Title singles-EML-well-52
Sample type SRA
 
Source name singles-EML
Organism Mus musculus
Characteristics cell line: EML
cell type: hematopoietic cells
treated with: none (untreated)
Growth protocol The mouse EML hematopoietic cells were grown in IMDM containing 20% horse serum, 2 mM L-Glutamine, 1% Pen/Strep and 100 ng/mL recombinant SCF (Peprotech).
Extracted molecule genomic DNA
Extraction protocol Single cells were captured using the C1 Single-Cell Auto Prep IFC microfluidic chips. Cells were permeabilized and accessible fragments were captured using 20 µL of Tn5 transposition mix (1.5x TD buffer, 1.5 µL transposease (Nextera DNA Sample Prep Kit, Illumina), 1x C1 Loading Reagent with low salt (Fluidigm), and 0.15% NP40) at 30 minutes at 37°C.
In a 96-well plate, 10 µL of harvested libraries were amplified in 50 µL PCR for an additional 14 cycles (1.25 µM custom Nextera dual-index PCR primers (Supplementary Table 1) in 1x NEBnext High-Fidelity PCR Master Mix) using the following PCR conditions: 72°C for 5min; 98°C for 30 s; and thermocycling at 98°C for 10 s, 72°C for 30 s, and 72°C for 1 min. The PCR products were pooled creating a final volume of ~4.8 mL. The pooled library was purified on a single MinElute PCR purification column (Qiagen) yielding libraries at an approximate concentration of ~1 µM. Libraries were quantified using qPCR prior to sequencing.
 
Library strategy OTHER
Library source genomic
Library selection other
Instrument model Illumina NextSeq 500
 
Description processed data file: single-EML.peaks.bed
Data processing library strategy: Single-cell ATAC-seq (scATAC-seq)
Adapter sequences were trimmed from FASTQs using custom python scripts to enable mapping fragments with sequences containing adapters. Paired-end reads were aligned to hg19 or mm10 using BOWTIE2 using the parameter –X2000 allowing fragments of up to 2 kb to align. Duplicates were removed using PICARD tools. Reads were subsequently filtered for alignment quality of >Q30 and were required to be properly paired. Reads mapping to the mitochondria, unmapped contigs and chromosome Y were removed and not considered.
We used MACS2 to call all reported ATAC-seq peaks. MACS2 was used with the following parameters (--nomodel --nolambda --keep-dup all --call-summits). Peaks were filtered using the consensus excludable ENCODE blacklist (http://hgdownload.cse.ucsc.edu/goldenPath/hg19/encodeDCC/wgEncodeMapability/) and a custom blacklist, designed to remove high-signal causing repeats and mitochondrial homologues. For all subsequent analysis we discarded peaks falling within these regions. Although we saw little effect on calculations of variability, in the case of K562 data, peaks were additionally filtered to exclude copy number amplifications. Using the filtered peak set, peak summits were extended +/-250 bps. The top 50,000 non-overlapping 500 bp summits are available here and were used for all downstream analysis.
Genome_build: hg19, mm10
Supplementary_files_format_and_content: Bam files across single-cells representing identical biological conditions have been merged. Reads pertaining to individual cells can be identified by their unique RGID tag corresponding to each assayed well. Bed files represent 500 bp peak summits as described above.
 
Submission date Jan 29, 2015
Last update date May 15, 2019
Contact name Jason Daniel Buenrostro
E-mail(s) jdbuenrostro@gmail.com
Organization name Broad Institute
Street address 415 Main Street
City Cambridge
State/province MA
ZIP/Postal code 02142
Country USA
 
Platform ID GPL19057
Series (1)
GSE65360 Single-cell chromatin accessibility data using scATAC-seq
Relations
BioSample SAMN03318332
SRA SRX860526

Supplementary data files not provided
SRA Run SelectorHelp
Raw data are available in SRA
Processed data are available on Series record

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