By Sample Peripheral Blood Mononuclear Primary Cells Track Settings
 
Peripheral Blood Mononuclear Primary Cells tracks for 8 assay type(s)

Track collection: Roadmap data by sample

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  Assay Type H3K36me3  Input  H3K9me3  H3K4me1  H3K9ac  MRE-Seq  H3K27me3  MeDIP-Seq 
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 H3K27me3  TC010  Peripheral_Blood_Mononuclear_Primary_Cells H3K27me3 Histone Modification by Chip-seq Signal from REMC/UCSF (Hotspot_Score=0.2764 Pcnt=69 DonorID:TC010)    Data format 
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 H3K36me3  TC010  Peripheral_Blood_Mononuclear_Primary_Cells H3K36me3 Histone Modification by Chip-seq Signal from REMC/UCSF (Hotspot_Score=0.4862 Pcnt=100 DonorID:TC010)    Data format 
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 H3K4me1  TC012  Peripheral_Blood_Mononuclear_Primary_Cells H3K4me1 Histone Modification by Chip-seq Signal from REMC/UCSF (Hotspot_Score=0.1534 Pcnt=7 DonorID:TC012)    Data format 
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 H3K9ac  TC010  Peripheral_Blood_Mononuclear_Primary_Cells H3K9ac Histone Modification by Chip-seq Signal from REMC/UCSF (Hotspot_Score=0.2855 Pcnt=66 DonorID:TC010)    Data format 
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 H3K9ac  TC012  Peripheral_Blood_Mononuclear_Primary_Cells H3K9ac Histone Modification by Chip-seq Signal from REMC/UCSF (Hotspot_Score=0.1502 Pcnt=17 DonorID:TC012)    Data format 
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 H3K9me3  TC010  Peripheral_Blood_Mononuclear_Primary_Cells H3K9me3 Histone Modification by Chip-seq Signal from REMC/UCSF (Hotspot_Score=0.1958 Pcnt=66 DonorID:TC010)    Data format 
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 H3K9me3  TC012  Peripheral_Blood_Mononuclear_Primary_Cells H3K9me3 Histone Modification by Chip-seq Signal from REMC/UCSF (Hotspot_Score=0.206 Pcnt=69 DonorID:TC012)    Data format 
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 Input  TC010  Peripheral_Blood_Mononuclear_Primary_Cells Input Histone Modification by Chip-seq Signal from REMC/UCSF (Hotspot_Score=0.0645 Pcnt=53 DonorID:TC010)    Data format 
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 Input  TC010  Peripheral_Blood_Mononuclear_Primary_Cells Input Histone Modification by Chip-seq Signal from REMC/UCSF (Hotspot_Score=0.0434 Pcnt=45 DonorID:TC010)    Data format 
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 Input  TC012  Peripheral_Blood_Mononuclear_Primary_Cells Input Histone Modification by Chip-seq Signal from REMC/UCSF (Hotspot_Score=0.0725 Pcnt=56 DonorID:TC012)    Data format 
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 MRE-Seq  TC003  Peripheral Blood Mononuclear Primary Cells DNA Methylation by MRE-seq Signal from REMC/UCSF-UBC (DonorID:TC003)    Data format 
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 MRE-Seq  TC007  Peripheral Blood Mononuclear Primary Cells DNA Methylation by MRE-seq Signal from REMC/UCSF-UBC (DonorID:TC007)    Data format 
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 MRE-Seq  TC009  Peripheral Blood Mononuclear Primary Cells DNA Methylation by MRE-seq Signal from REMC/UCSF-UBC (DonorID:TC009)    Data format 
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 MeDIP-Seq  TC003  Peripheral Blood Mononuclear Primary Cells DNA Methylation by MeDIP-seq Signal from REMC/UCSF-UBC (Hotspot_Score=0.3758 Pcnt=66 DonorID:TC003)    Data format 
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 MeDIP-Seq  TC007  Peripheral Blood Mononuclear Primary Cells DNA Methylation by MeDIP-seq Signal from REMC/UCSF-UBC (Hotspot_Score=0.0094 Pcnt=30 DonorID:TC007)    Data format 
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 MeDIP-Seq  TC009  Peripheral Blood Mononuclear Primary Cells DNA Methylation by MeDIP-seq Signal from REMC/UCSF-UBC (Hotspot_Score=0.2531 Pcnt=50 )    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