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Colonic Mucosa tracks for 9 assay type(s)

Track collection: Roadmap data by sample

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  Assay Type H3K36me3  H3K4me3  Input  H3K9me3  H3K4me1  H3K27ac  H3K9ac  RRBS  H3K27me3 Assay Type  
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 H3K27ac  155  BI Colonic Mucosa Histone H3K27ac Donor 155 Library DNA_Lib 1047 EA Release 9    Data format 
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 H3K27ac  32  BI Colonic Mucosa Histone H3K27ac Donor 32 Library DNA_Lib 1045 EA Release 9    Data format 
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 H3K27me3  155  BI Colonic Mucosa Histone H3K27me3 Donor 155 Library DNA_Lib 364 EA Release 6    Data format 
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 H3K27me3  32  Colonic Mucosa H3K27me3 Histone Modification by Chip-seq Signal from REMC/Broad (Hotspot_Score=0.1847 Pcnt=44 DonorID:32)    Data format 
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 H3K36me3  155  BI Colonic Mucosa Histone H3K36me3 Donor 155 Library DNA_Lib 365 EA Release 6    Data format 
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 H3K36me3  32  Colonic Mucosa H3K36me3 Histone Modification by Chip-seq Signal from REMC/Broad (Hotspot_Score=0.2745 Pcnt=55 DonorID:32)    Data format 
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 H3K4me1  155  BI Colonic Mucosa Histone H3K4me1 Donor 155 Library DNA_Lib 363 EA Release 6    Data format 
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 H3K4me1  32  Colonic Mucosa H3K4me1 Histone Modification by Chip-seq Signal from REMC/Broad (Hotspot_Score=0.31 Pcnt=30 DonorID:32)    Data format 
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 H3K4me3  155  BI Colonic Mucosa Histone H3K4me3 Donor 155 Library DNA_Lib 366 EA Release 6    Data format 
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 H3K4me3  32  Colonic Mucosa H3K4me3 Histone Modification by Chip-seq Signal from REMC/Broad (Hotspot_Score=0.4897 Pcnt=67 DonorID:32)    Data format 
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 H3K9ac  155  BI Colonic Mucosa Histone H3K9ac Donor 155 Library DNA_Lib 367 EA Release 6    Data format 
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 H3K9ac  32  Colonic Mucosa H3K9ac Histone Modification by Chip-seq Signal from REMC/Broad (Hotspot_Score=0.2838 Pcnt=63 DonorID:32)    Data format 
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 H3K9me3  155  BI Colonic Mucosa Histone H3K9me3 Donor 155 Library DNA_Lib 368 EA Release 6    Data format 
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 H3K9me3  32  Colonic Mucosa H3K9me3 Histone Modification by Chip-seq Signal from REMC/Broad (Hotspot_Score=0.1436 Pcnt=42 DonorID:32)    Data format 
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 Input  155  BI Colonic Mucosa ChIP-Seq Input Donor 155 Library DNA_Lib 369 EA Release 6    Data format 
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 Input  32  Colonic Mucosa Input Histone Modification by Chip-seq Signal from REMC/Broad (Hotspot_Score=0.0221 Pcnt=36 DonorID:32)    Data format 
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 RRBS  32  Colonic_Mucosa DNA Methylation by RRBS Signal from REMC/Broad (DonorID:32)    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