Sample Summary CD4 Naive Primary Cells Summary Track Settings
 
Roadmap Epigenome CD4 Naive Primary Cells Summary for 11 assay type(s)

Track collection: Sample Summary

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     CD4N H3K27ac 100  CD4 Naive Primary Cells H3K27ac Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.4112 Pcnt=82)    Data format 
     CD4N H3K27ac 101  CD4 Naive Primary Cells H3K27ac Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.3593 Pcnt=76)    Data format 
     CD4N H3K27me3 100  CD4 Naive Primary Cells H3K27me3 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.1001 Pcnt=29)    Data format 
     CD4N H3K27me3 101  CD4 Naive Primary Cells H3K27me3 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.1056 Pcnt=35)    Data format 
     CD4N H3K36me3 01  CD4_Naive_Primary_Cells Cell Line H3K36me3 Histone Modification by Chip-seq Signal from REMC/UCSF (Hotspot_Score=0.3205 Pcnt=70 DonorID:TC001)    Data format 
     CD4N H3K36me3 100  CD4 Naive Primary Cells H3K36me3 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.146 Pcnt=16)    Data format 
     CD4N H3K36me3 101  CD4 Naive Primary Cells H3K36me3 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.161 Pcnt=27)    Data format 
     CD4N H3K4me1 100  CD4 Naive Primary Cells H3K4me1 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.3304 Pcnt=57)    Data format 
     CD4N H3K4me1 101  CD4 Naive Primary Cells H3K4me1 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.3245 Pcnt=48)    Data format 
     CD4N H3K4me3 100  CD4 Naive Primary Cells H3K4me3 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.2442 Pcnt=35)    Data format 
     CD4N H3K4me3 101  CD4 Naive Primary Cells H3K4me3 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.1556 Pcnt=13)    Data format 
     CD4N H3K9ac 01  CD4_Naive_Primary_Cells Cell Line H3K9ac Histone Modification by Chip-seq Signal from REMC/UCSF (Hotspot_Score=0.2771 Pcnt=60 DonorID:TC001)    Data format 
     CD4N H3K9me3 100  CD4 Naive Primary Cells H3K9me3 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.0748 Pcnt=27)    Data format 
     CD4N H3K9me3 101  CD4 Naive Primary Cells H3K9me3 Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.0712 Pcnt=20)    Data format 
     CD4N Input 100  CD4 Naive Primary Cells Input Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.0228 Pcnt=69)    Data format 
     CD4N Input 101  CD4 Naive Primary Cells Input Histone Modification by Chip-seq Signal from REMC/Broad (HOTSPOT_SCORE=0.0162 Pcnt=59)    Data format 
     CD4N MeDIP 03  CD4 Naive Primary Cells DNA Methylation by MeDIP-seq Signal from REMC/UCSF-UBC (Hotspot_Score=0.2893 Pcnt=29 DonorID:TC003)    Data format 
     CD4N MeDIP 07  CD4 Naive Primary Cells DNA Methylation by MeDIP-seq Signal from REMC/UCSF-UBC (Hotspot_Score=0.4174 Pcnt=83 DonorID:TC007)    Data format 
     CD4N MeDIP 09  CD4 Naive Primary Cells DNA Methylation by MeDIP-seq Signal from REMC/UCSF-UBC (Hotspot_Score=0.1658 Pcnt=20 )    Data format 
     CD4N MRE 03  CD4 Naive Primary Cells DNA Methylation by MRE-seq Signal from REMC/UCSF-UBC (DonorID:TC003)    Data format 
     CD4N MRE 07  CD4 Naive Primary Cells DNA Methylation by MRE-seq Signal from REMC/UCSF-UBC (DonorID:TC007)    Data format 
     CD4N MRE 09  CD4 Naive Primary Cells DNA Methylation by MRE-seq Signal from REMC/UCSF-UBC (DonorID:TC009)    Data format 
     CD4N mRNA 14  CD4 Naive Primary Cell mRNA 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