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CD4 Memory Primary Cells tracks for 11 assay type(s)

Track collection: Roadmap data by sample

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  Assay Type H3K4me3  H3K36me3  MeDIP-Seq  Input  H3K4me1  smRNA-Seq  H3K9me3  H3K27ac  MRE-Seq  H3K27me3  mRNA-Seq Assay Type  
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 H3K27ac  100  CD4 Memory Primary Cells H3K27ac Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.4878 Pcnt=94)    Data format 
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 H3K27ac  101  CD4 Memory Primary Cells H3K27ac Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.2622 Pcnt=53)    Data format 
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 H3K27me3  100  CD4 Memory Primary Cells H3K27me3 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.1046 Pcnt=33)    Data format 
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 H3K27me3  101  CD4 Memory Primary Cells H3K27me3 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.0756 Pcnt=8)    Data format 
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 H3K36me3  100  CD4 Memory Primary Cells H3K36me3 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.1505 Pcnt=20)    Data format 
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 H3K36me3  101  CD4 Memory Primary Cells H3K36me3 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.0641 Pcnt=6)    Data format 
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 H3K4me1  100  CD4 Memory Primary Cells H3K4me1 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.4449 Pcnt=83)    Data format 
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 H3K4me1  101  CD4 Memory Primary Cells H3K4me1 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.297 Pcnt=31)    Data format 
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 H3K4me3  100  CD4 Memory Primary Cells H3K4me3 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.0994 Pcnt=4)    Data format 
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 H3K4me3  101  CD4 Memory Primary Cells H3K4me3 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.2395 Pcnt=31)    Data format 
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 H3K4me3  20  CD4 Memory Primary Cells H3K4me3 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.3634 Pcnt=63)    Data format 
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 H3K9me3  100  CD4 Memory Primary Cells H3K9me3 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.0739 Pcnt=24)    Data format 
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 H3K9me3  101  CD4 Memory Primary Cells H3K9me3 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.051 Pcnt=10)    Data format 
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 Input  100  CD4 Memory Primary Cells Input Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.0042 Pcnt=20)    Data format 
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 Input  101  CD4 Memory Primary Cells Input Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.0048 Pcnt=28)    Data format 
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 Input  20  CD4 Memory Primary Cells Input Histone Modification by Chip-seq Signal from REMC/Broad (Hotspot_Score=0.0599 Pcnt=47 DonorID:20)    Data format 
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 MRE-Seq  TC003  CD4 Memory Primary Cells DNA Methylation by MRE-seq Signal from REMC/UCSF-UBC (DonorID:TC003)    Data format 
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 MRE-Seq  TC007  CD4 Memory Primary Cells DNA Methylation by MRE-seq Signal from REMC/UCSF-UBC (DonorID:TC007)    Data format 
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 MRE-Seq  TC009  CD4 Memory Primary Cells DNA Methylation by MRE-seq Signal from REMC/UCSF-UBC    Data format 
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 MeDIP-Seq  TC003  CD4 Memory Primary Cells DNA Methylation by MeDIP-seq Signal from REMC/UCSF-UBC (Hotspot_Score=0.201 Pcnt=12 DonorID:TC003)    Data format 
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 MeDIP-Seq  TC007  CD4 Memory Primary Cells DNA Methylation by MeDIP-seq Signal from REMC/UCSF-UBC (Hotspot_Score=0.3391 Pcnt=50 DonorID:TC007)    Data format 
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 MeDIP-Seq  TC009  CD4 Memory Primary Cells DNA Methylation by MeDIP-seq Signal from REMC/UCSF-UBC (Hotspot_Score=0.2001 Pcnt=30 )    Data format 
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 mRNA-Seq  TC014  CD4 Memory Primary Cell mRNA Signal from REMC/UCSF-UBC    Data format 
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 smRNA-Seq  TC014  CD4M smRNA TC014 smRNA-seq Signal from REMC/UCSF-UBC    Data format 
    
Assembly: Human Feb. 2009 (GRCh37/hg19)

Vizhub @ Wash U built this track, and Roadmap Epigenomics Consortium is responsible for its contents.

Description

These tracks are genome-wide DNA methylation maps generated by Roadmap Epigenomics Project. Each track is collection of DNA methylation experiment data on one sample type.

DNA methylation of human DNA mostly happens on cytosine bases of CpG dinucleotides. The methylated DNA usually prevent accessibility of regulatory proteins and hampers transcription, while unmethylated DNA is usually indicative of open chromatin. The MeDIP-Seq and MRE-Seq experiments are usually performed on same sample to identify genome-wide DNA methylation pattern. MeDIP-Seq (methylated DNA immunoprecipitation and sequencing) is a ChIP-based approach utilizing antibody against methylated cytosine. This method enriches methylated DNA and high read count indicates high likelihood of underlying region is methylated. The MRE-Seq (methylation restriction enzyme sequencing) uses methylation-sensitive restriction enzymes to digest DNA, and only cut at unmethylated restriction sites. The cut restriction sites will be detected by sequencing where reads aligned to a restriction site on reference genome means the restriction site is unmethylated.

The MethylC-Seq (MethylC sequencing) uses bisulfite to convert methylated cytosines to thymines before sequencing. The percentage of reads with a T versus a C indicates the percentage methylation at the cytosine. Details can be found in this paper Lister R, et al., Nature. 2009 Nov 19;462(7271):315-22. .

RRBS (Reduced-Representation-Bisulfite-Sequencing) is similar to MethylC-seq except RRBS uses restriction enzyme to fragment the genome into fragments suitably-sized for sequencing. While RRBS produces percent methylation similar to MethylC-seq, it is limited to cytosines that are within restriction fragments of a suitable size and tend to measure CpG dense regions only. Details can be found in this paper: Meissener, A. et al., Nucleic Acids Res. 2005; 33(18): 5868-5877. .

Display conventions

Each track can be turned on/off individually. Inside each track, sub-tracks are displayed in same vertical space and are overlayed with transparent colors for contrast. All tracks displays read density data in form of wiggle plots. Number of aligned reads is counted at each base pair, and a summarized value is computed for each 20 bp interval for display. Sub-tracks sharing same space use same scale.

Methods

Experimental protocols: follow this link for experimental protocols.

Data processing: EDACC carried out data processing and quality assessment. Details are fully explained here . In brief, sequencing reads were aligned with 'Pash' program to derive read density data. The read density data is prepared into 'wiggle' format files with fixed step length of 20 bp. Data in wiggle and other formats have been deposited in NCBI Gene Expression Omnibus database for public access.

Quality control: the HotSpot was one of the methods used to assess quality of MeDIP-Seq experiments. The long track name includes a "Hotspot_Score" field indicates the percentage of sequencing reads found inside hotspot regions. The "Pcnt" field shows the percentile of current experiment score in all MeDIP-Seq experiments. This value is subject to change in next Data Release. The most comprehensive and up-to-date description on QC Metrics used by the consortium can be found here .

Release Notes

The data is combination of Release II, III, IV, V, VI, VII, VIII and IX which were mapped to human reference genome version hg19. The data is production of Roadmap Epigenomics Project.

Please follow the link for Roadmap Epigenomics data access policy

Credits

These data were generated in labs from three institutions: UCSF, UBC, UCSD as part of Roadmap Epigenomics Project.

Useful links