Introduction to differential binding Peter Humburg Statistician, - PowerPoint PPT Presentation

DataCamp ChIP-seq Workflows in R CHIP - SEQ WORKFLOWS IN R Introduction to differential binding Peter Humburg Statistician, Macquarie University

DataCamp ChIP-seq Workflows in R

DataCamp ChIP-seq Workflows in R Comparing samples Two groups of samples: Primary and treatment resistant tumor. Questions we would like to answer: Are samples from the same group generally similar? Are samples from different groups different? What are those differences?

DataCamp ChIP-seq Workflows in R

DataCamp ChIP-seq Workflows in R

DataCamp ChIP-seq Workflows in R

DataCamp ChIP-seq Workflows in R

DataCamp ChIP-seq Workflows in R PCA plots for ChIP-seq data qc_result <- ChIPQC("sample_info.csv", "hg19") counts <- dba.count(qc_results, summits=250) plotPrincomp(counts)

DataCamp ChIP-seq Workflows in R Hierarchical clustering Compute distance between samples distance <- dist(t(coverage)) Create dendogram dendro <- hclust(distance) Plot dendrogram plot(dendro)

DataCamp ChIP-seq Workflows in R Heatmaps Create heatmap from coverage data for peaks dba.plotHeatmap(peaks, maxSites = peak_count, correlations = FALSE)

DataCamp ChIP-seq Workflows in R CHIP - SEQ WORKFLOWS IN R Let's practice!

DataCamp ChIP-seq Workflows in R CHIP - SEQ WORKFLOWS IN R Testing for differential binding Peter Humburg Statistician, Macquarie University

DataCamp ChIP-seq Workflows in R Comparing groups of ChIP-seq samples Use statistical analysis of read counts to identify significant differences between groups. DiffBind package provides interface to analysis tools. Use either DESeq2 or edgeR.

DataCamp ChIP-seq Workflows in R Creating a shared peak set Counting reads in peak set: peak_counts <- dba.counts(qc_output, summits=250)

DataCamp ChIP-seq Workflows in R Establishing a contrast Creating a contrast: peak_counts <- dba.contrast(peak_counts, categories = DBA_CONDITION) Other supported categories: DBA_ID DBA_TISSUE DBA_FACTOR DBA_TREATMENT DBA_REPLICATE DBA_CALLER

DataCamp ChIP-seq Workflows in R Using controls

DataCamp ChIP-seq Workflows in R Running the analysis bind_diff <- dba.analyze(peak_counts)

DataCamp ChIP-seq Workflows in R A first look at the results PCA plot for differentially bound peaks dba.plotPCA(bind_diff, DBA_Condition, contrast=1) Heatmap for differentially bound peaks dba.plotHeatmap(bind_diff, DBA_Condition, contrast=1)

DataCamp ChIP-seq Workflows in R CHIP - SEQ WORKFLOWS IN R Let's practice!

DataCamp ChIP-seq Workflows in R CHIP - SEQ WORKFLOWS IN R A closer look at differential binding Peter Humburg Statistician, Macquarie University

DataCamp ChIP-seq Workflows in R Creating MA plots with DiffBind dba.plotMA(dba_object)

DataCamp ChIP-seq Workflows in R

DataCamp ChIP-seq Workflows in R

DataCamp ChIP-seq Workflows in R Creating Volcano plots with DiffBind dba.plotVolcano(dba_object)

DataCamp ChIP-seq Workflows in R

DataCamp ChIP-seq Workflows in R Creating Box plots with DiffBind dba.plotBox(dba_object)

DataCamp ChIP-seq Workflows in R

DataCamp ChIP-seq Workflows in R CHIP - SEQ WORKFLOWS IN R Let's practice!