ALTRE: Workflow: Post-alignment to altered enhancers and promoters

In ewymathe/testALTREinstall: Workflow for Identifying Regulatory Elements from Chromatin Accessibility Assay Data

Description

This workflow takes aligned reads and peak/hotspot calls from assays of open chromatin (ATAC-seq and Dnase-seq) and identifies regions (enhancers and promoters) that differ based on cell and tissue type.

Details

ALTRE requires sample information CSV file, peak files (bed format), and alignment bam files (BAM) as input

Workflow Steps: The following is the order in which the functions should be used: (Click on function to get more detailed information)

1. loadBedFiles

   Takes in a sample information file (CSV), loads peak files, and outputs a GRangesList object that holds all peaks for each sample type.

2. getConsensusPeaks

   Takes in a sample peaks list (output from loadBedFiles in step 2), and outputs consensus peaks. Consensus peaks are those present in at least N replicates. A barplot summary of the number of consensus peaks and those in each replicate, use plotConsensusPeaks().

3. combineAnnotatePeaks

   The GRanges for all sample types from the previous step are combined and annotated with type specificity (which cell types the hotspot is present in) and whether each region represented in the GRanges is a promoter (default: <1500bp from a transcription start site) or an enhancer (>1500bp from a transcription start site). Function can also merge regulatory regions that are within a specified distance from each other. This function requires the annotation of transcription start sites (e.g. to retrieve from Ensembl, run TSS <- getTSS()))

4. getCounts

   The number of reads overlapping all regions for each cell type is calculated. To view a density plot of the sizes of the regions, use the function plotgetcounts().

5. countanalysis

   Identify significantly altered regulatory elements (promoters or enhancers). A volcano plot of these significantly altered regulatory elements can be viewed by running the function plotCountAnalysis().

6. comparePeaksAltre

   This function compares the number of regulatory regions identified as altered or shared between two sample types. The two methods compared are: 1) using peak presence and associated intensity (e.g. amount of chromatin accessibility); 2) using peak presence only as determined by peak/hotspot caller.

7. pathenrich

   Determine which pathways are overrepresented in altered promoters and enhancers.

ewymathe/testALTREinstall documentation built on May 16, 2019, 9:42 a.m.