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Sample GSM3686966 Query DataSets for GSM3686966
Status Public on Nov 17, 2019
Title U-937_gDNA-ChIP
Sample type SRA
Source name U-937_gDNA-ChIP
Organism Homo sapiens
Characteristics cell line: U-937
tissue/cell type: histiocytic lymphoma cell line
chip antibody: none
Growth protocol Cells were cultured in RPMI 1640 (Gibco; routinely supplemented with 2 mM L-glutamine (Biochrom), 1 mM sodium pyruvate (Sigma), 50 U/ml penicillin/streptomycin, 0.4x vitamins (Sigma), 1x non-essential amino acids (Sigma), 50 μM b-mercaptoethanol (Gibco)) supplemented with 10% heat inactivated fetal bovine serum.
Collection of blood cells from healthy donors was performed in compliance with the Helsinki Declaration. All donors signed an informed consent. The leukapheresis procedure and subsequent purification of hematopoietic cell types were approved by the local ethical committee (reference number 12-101-0260). Human mast cell were purified from skin that was obtained from cosmetic breast-reduction surgeries (Motakis et al., 2014) with informed consent of the patients. Mast cell preparations were performed in compliance with the Helsinki Declaration, and approved by the ethics committee of the Charité Universitätsmedizin Berlin (reference number EA1/204/10).
Extracted molecule genomic DNA
Extraction protocol ChIPseq was essentially done as described (Pham et al. 2012).
Libraries were generated as described (Pham et al. 2012)
Library strategy ChIP-Seq
Library source genomic
Library selection ChIP
Instrument model Illumina HiSeq 1000
Description Genomic DNA (control)
Data processing Raw data were aligned to the human genome (GRCh37/hg19) using bowtie2 (Langmead and Salzberg, 2012) in very sensitive mode, keeping only reads that map to a single unique genomic location for further analysis (MAPQ > 10).
Bigwigs of ChIPseq data sets were generated using HOMER v4.9 (Heinz et al, 2010) and standard settings. For cancer cell lines, we used the Control-FREEC v11.0 program to determine allelic imbalances from low-depth whole genome sequencing data and corrected ChIP-seq read counts accordingly to generate CNV-corrected bigWigs.
ChIP-seq peaks were called using HOMER?s findPeaks program in ??factor?? mode using default parameters (standard) or with -fdr 0.00001 (stringent) to identify focal peaks. Stringent peaks were further filtered for a minimal normalized tag count of 15 tags per peak. All peak sets were filtered by subtracting blacklisted genomic regions 49, and by filtering out regions with a mappability <0.8. The latter was annotated to peak regions from mappability tracks generated with the GEM package using HOMER?s
Genome_build: hg19
Supplementary_files_format_and_content: ChIPseq tracks in bigWig format (before and after CNV normalization
Supplementary_files_format_and_content: ChIPseq peaks (called using standard or stringent parameters)
Submission date Mar 25, 2019
Last update date Nov 19, 2019
Contact name Michael Rehli
Organization name University Hospital Regensburg
Department Internal Med III
Street address F.-J.-Strauss-Allee 11
City Regensburg
ZIP/Postal code 93042
Country Germany
Platform ID GPL15433
Series (2)
GSE128834 The hematopoietic master transcription factor PU.1 requires its interaction with the SWI/SNF remodeler to access chromatin de novo [ChIP-seq]
GSE128837 The hematopoietic master transcription factor PU.1 requires its interaction with the SWI/SNF remodeler to access chromatin de novo
BioSample SAMN11252891
SRA SRX5574388

Supplementary file Size Download File type/resource
GSM3686966_U-937_gDNA-ChIP.bigwig 133.3 Mb (ftp)(http) BIGWIG
SRA Run SelectorHelp
Raw data are available in SRA
Processed data provided as supplementary file

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