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Hi all,
I'm new to this forum and to NGS in general. Currently, I'm mainly interessted in ChIP-Seq data analysis of histone modifications, with the usual problems of normalization, peak finding, and detection of differential modifications in different samples. Ideally, would like to use a model where input DNA and replicats can be included. I already had a look at BaySeq and DESeq, which are however designed for RNA-Seq and a peak should - if I understand correctly - be represented by a single count. Not sure, if that would do the job. In addition, BaySeq uses a scaling factor to correct for different library sizes, however, I suppose a different normalization scheme would be more appropriate. Any advice, comments wellcome
cheers
EdinG
I'm new to this forum and to NGS in general. Currently, I'm mainly interessted in ChIP-Seq data analysis of histone modifications, with the usual problems of normalization, peak finding, and detection of differential modifications in different samples. Ideally, would like to use a model where input DNA and replicats can be included. I already had a look at BaySeq and DESeq, which are however designed for RNA-Seq and a peak should - if I understand correctly - be represented by a single count. Not sure, if that would do the job. In addition, BaySeq uses a scaling factor to correct for different library sizes, however, I suppose a different normalization scheme would be more appropriate. Any advice, comments wellcome
cheers
EdinG