tag:blogger.com,1999:blog-4376119613549496246.post4889850239448599435..comments2024-03-27T23:36:17.389-07:00Comments on Diving into Genetics and Genomics: library size normalization for ChIP-seqtommyhttp://www.blogger.com/profile/04023008941349107659noreply@blogger.comBlogger1125tag:blogger.com,1999:blog-4376119613549496246.post-73986616639782664972018-12-21T09:43:52.736-08:002018-12-21T09:43:52.736-08:00Hi Tommy!
First and foremost, thank you for this ...Hi Tommy!<br /><br />First and foremost, thank you for this wonderful blog! When I started learning and ultimately applying bioinformatics to my own research, this was really an important source for me. <br /><br />I was wondering. I'm interested in doing differential ChIP binding analysis with multiple replicates. I was planning to use DESeq2 ater removing the Greylists from the inputs (per Gord Brown), but I did want to try Diffbind too, but as you mentioned in your post, my concern is downloading all the bamfiles into my computer to use in R and it may be too memory demanding. Now that I see you've done a Diffbind analysis, how did you overcome this problem? <br /><br />Also this is my current plan for the analysis - perfrom ChIPGreyLists on Inputs, remove those regions from the respective IP bam files, call peaks, make a count table, and do DESeq2. Are the parameters for the DESeq2 analysis the same as for regular RNA seq or do I have to change something?<br /><br />Thank you again for this website!<br /><br />YonatanYonatan Amzaleghttps://www.blogger.com/profile/06810427270516930212noreply@blogger.com