![]() # 11 ZR752 ZR75 ER Responsive Full-Media 2 # 10 ZR751 ZR75 ER Responsive Full-Media 1 # 9 MCF7r2 MCF7 ER Resistant Full-Media 2 # 8 MCF7r1 MCF7 ER Resistant Full-Media 1 # 7 T47D2 T47D ER Responsive Full-Media 2 # 6 T47D1 T47D ER Responsive Full-Media 1 # 5 MCF73 MCF7 ER Responsive Full-Media 3 # 4 MCF72 MCF7 ER Responsive Full-Media 2 # 3 MCF71 MCF7 ER Responsive Full-Media 1 # 2 BT4742 BT474 ER Resistant Full-Media 2 # 1 BT4741 BT474 ER Resistant Full-Media 1 # SampleID Tissue Factor Condition Treatment Replicate # Loading required package: GenomicAlignments # The following object is masked from 'package:BiocGenerics': # rbind, Reduce, rep.int, rownames, sapply, setdiff, sort, # order, paste, pmax, pmax.int, pmin, pmin.int, Position, rank, # intersect, is.unsorted, lapply, Map, mapply, match, mget, # colnames, do.call, duplicated, eval, evalq, Filter, Find, get, # anyDuplicated, append, as.ame, as.vector, cbind, # The following objects are masked from 'package:base': # The following object is masked from 'package:stats': # parLapplyLB, parRapply, parSapply, parSapplyLB # clusterExport, clusterMap, parApply, parCapply, parLapply, # clusterApply, clusterApplyLB, clusterCall, clusterEvalQ, # The following objects are masked from 'package:parallel': # Loading required package: GenomicRanges We check the files in the DiffBind folder, and in the peaks subdirectory: This package is useful for manipulating ChIP-seq signal in R, for comparing signal across files and for performing tests of diffential binding. #4PEAKS DNA WIKIPEDIA CODE#The following lab will go over the functionality of the DiffBind package, mostly using code from the vignette. These are biologically meaningful, as a number of proteins which are bound to DNA have conformations which make certain strings of DNA letters more preferable for binding. Motif-finding refers to the task of looking for common strings of DNA letters contained within peaks. Motif-finding is common ChIP-seq analysis which is not explored in this course, as we do not cover the basics of analysis of sequences. In this lab we will focus on differential binding across samples, by focusing on the peak regions and counting the number of ChIP-seq reads which fall into the peaks for each sample. After peak callingĪ number of analyses might be of interest following peak calling. As mentioned in the lecture, for ChIP of proteins with broad peaks (such as modified histones), algorithms other than those for detecting sharp peaks might perform better. There are many different algorithms for calling peaks, which have varying performance on different kinds of experiments. The code for this is in the MACS.txt file. #4PEAKS DNA WIKIPEDIA SOFTWARE#In the first lab, we use the MACS software to call peaks. More specifically, ChIP-seq results in two peaks of reads of different strands (plus/minus also referred to as Watson/Crick), as shown in Figure 1 of the MACS manuscript: Zhang 2008 Peak calling The raw data looks quite different than DNA- or RNA-seq, in that the NGS reads form tall “peaks” at the locations where the proteins were tightly bound to DNA in the cells which were used to create the sample. ChIP-seq is a protocol for inferring the locations of proteins bound or associated with DNA. ![]()
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