IronMan | study non-promoter H3K4me3 in K562
kandi X-RAY | IronMan Summary
kandi X-RAY | IronMan Summary
IronMan is a HTML library. IronMan has no bugs, it has no vulnerabilities and it has low support. You can download it from GitHub.
there are many study of H3K4me3 in promoter region. but almost didn’t find the study of H3K4me3. we found that most H3K4me3 are in Promoter region in hESC, and there are an increase in non-promoter region in other cell lines. many of these non-promoter H3K4me3 co-occur with H3K4me1 and H3K27ac, which usually defined as active enhancer. they are short than the H3K4me3 peaks in promoter, which have studied that the genes with long H3K4me3 have stable expression. And they are cell-type specific. second part: ~~~~~~. 1.genomic distribution in different cell lines(so I need their peaks by runing Macs under the same condition). 2.seperate peaks as promoter peaks and non-promoter peaks, look into their overlapping in different cell lines, respectively. #Data~~read all bed-like file by GRange format(1 base) macs output file xls(1 base),bed(0 base) *macs2 output file ChIP-Seq H3K4me3(H1,K562,Helas3,Hmec,Nha,Nhdfad,Nhek,Nhlf) H3K4me1(H1,K562) H3K27ac(H1,K562,Helas3,Hmec,Nhek). #report three part H3K4me3 distribution with the same p-value cutoff among different cell types H3K4me3 distribution with the same peak numbers among different cell types. H3K4me3 common in promoter and specific in non-promoter.
there are many study of H3K4me3 in promoter region. but almost didn’t find the study of H3K4me3. we found that most H3K4me3 are in Promoter region in hESC, and there are an increase in non-promoter region in other cell lines. many of these non-promoter H3K4me3 co-occur with H3K4me1 and H3K27ac, which usually defined as active enhancer. they are short than the H3K4me3 peaks in promoter, which have studied that the genes with long H3K4me3 have stable expression. And they are cell-type specific. second part: ~~~~~~. 1.genomic distribution in different cell lines(so I need their peaks by runing Macs under the same condition). 2.seperate peaks as promoter peaks and non-promoter peaks, look into their overlapping in different cell lines, respectively. #Data~~read all bed-like file by GRange format(1 base) macs output file xls(1 base),bed(0 base) *macs2 output file ChIP-Seq H3K4me3(H1,K562,Helas3,Hmec,Nha,Nhdfad,Nhek,Nhlf) H3K4me1(H1,K562) H3K27ac(H1,K562,Helas3,Hmec,Nhek). #report three part H3K4me3 distribution with the same p-value cutoff among different cell types H3K4me3 distribution with the same peak numbers among different cell types. H3K4me3 common in promoter and specific in non-promoter.
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