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Sample GSM1597101

Query DataSets for GSM1597101

Status

Public on Jun 17, 2015

Title

singles-K562-rep3-well-175

Sample type

SRA

Source name

singles-K562-rep3

Organism

Homo sapiens

Characteristics

cell line: K562
cell type: chronic myeloid leukemia cells
treated with: none (untreated)

Biomaterial provider

ATCC

Growth protocol

K562 (ATCC) chronic myeloid leukemia cells were maintained in Iscove’s modified Dulbecco’s medium (IMDM) containing 10% FBS (HyClone, Thermo Scientific) and 1% Penicillin Streptomycin (Pen/Strep).

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 HiSeq 2500

Description

processed data file: single-K562.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

Oct 17, 2019

Contact name

Jason Daniel Buenrostro

E-mail(s)

[email protected]

Organization name

Broad Institute

Street address

415 Main Street