In MPIIComputationalEpigenetics/epiRepeatR: epiRepeatR

Analyzing the Epigenetics of Repetitive Elements with epiRepeatR

February 12, 2016

Installation and set up

epiRepeatR can be directly installed from github

library(devtools)
install_github("MPIIComputationalEpigenetics/epiRepeatR")

You need the following additional programs installed on your system:

• samtools can be obtained from http://samtools.sourceforge.net/
• For bisulfite alignment: bsmap can be obtained from https://code.google.com/archive/p/bsmap/
• For ChIP-seq alignment: bwa can be obtained from http://bio-bwa.sourceforge.net/

You also need to make sure the executables can be found (i.e. by including them in your PATH variable).

Preliminaries

Loading the epiRepeatR package

library(epiRepeatR)

Preparing the repeat reference

First, get the appropiate fasta file for the genome of your choice following these setps:

1. Go to http://www.girinst.org/repbase/
2. If you did not already do this, register (free)
3. On the main page: click on "Browse RU"
4. Change to fasta format
5. Select apropriate taxon
6. Download [Taxon] and ancestral (shared) repeats. You need to specify your RepBase username and password.

Epigenome analysis of repetitive elements

Configuring the analysis

Preparing the analysis annotation

Input files and annotations for the various epigenetic marks at various levels are specified in file annotation tables. They are specified as tab-separated files with a header line. Here's an example:

fileName | sampleName | mark | dataType | healthStatus | analysisStep --- | --- | --- | --- | --- | --- sample01_WGBS.bam | sample01 | DNAmeth | WGBS | control | seqReads sample01_Input.bam | sample01 | Input | Input | control | seqReads sample01_H3K9me3.bam | sample01 | H3K9me3 | ChIPseq | control | seqReads sample01_H3K4me3.bam | sample01 | H3K4me3 | ChIPseq | control | seqReads sample02_WGBS.bam | sample02 | DNAmeth | WGBS | control | seqReads sample02_Input.bam | sample02 | Input | Input | control | seqReads sample02_H3K9me3.bam | sample02 | H3K9me3 | ChIPseq | control | seqReads sample02_H3K4me3.bam | sample02 | H3K4me3 | ChIPseq | control | seqReads sample03_WGBS.bam | sample03 | DNAmeth | WGBS | sick | seqReads sample03_Input.bam | sample03 | Input | Input | sick | seqReads sample03_H3K9me3.bam | sample03 | H3K9me3 | ChIPseq | sick | seqReads sample03_H3K4me3.bam | sample03 | H3K4me3 | ChIPseq | sick | seqReads

Each row must contain the following columns:

Column name | Description --- | --- fileName | Location of the file on disc sampleName | identifier of the sample the file belongs to mark | epigenetic mark that is being assayed. Can be anything, but has to be consistent for later annotation dataType | WGBS or RRBS for bisulfite sequencing. ChIPseq for immunoprecipitation signal and Input for input/whole cell extract from ChIP-seq experiments. Can also be MergedInput for a common input to normalize ChIP-seq experiments against. analysisStep | Which analysis step does the file belong to. See table below for possible values.

All other columns (such as healthStatus in the example above) are considered annotation that can be used for sample grouping.

Typically, you will start from sequencing reads in BAM format (aligned or unaligned). In this case specify seqReads as analysis step. However, you can also input files from intermediate steps of the repeat analysis if you have them available. Here is a list of analysis steps and associated file types that can be used as input:

analysisStep | Description --- | --- seqReads | Sequencing reads in aligned or unaligned BAM file from which applicable reads will be extracted and filtered from. bamExtract | Sequencing reads in aligned or unaligned BAM file which have already been extracted. No filtering step is conducted. mergeChipInput | Common input to be used as reference to normalize all ChIP-seq experiments to. Typically created by joining multiple Input BAM files into a common one repeatAlignment | Sequencing reads already aligned to the reference of repetitive elements as BAM file. methCalling | R dataset file (RDS) of called methylation levels for each repetitive element CpG computed from repeat alignments. chipQuantification | R dataset file (RDS) of quantified ChIP-seq enrichment scoress for each repetitive elemen from repeat alignments.

Setting analysis options

You can configure the analysis using config files. They are specified in JSON format and look like this:

{
  "refFasta": "Homo_sapiens_all.fa",
  "species": "human",
  "tempDir": "temp",
  "n.processes": 0,
  "samtools.exec": "samtools",
  "inputBam.mappingStatus": "all",
  "chip.mergeInput": false,
  "aligner.chip": "chip_bwa",
  "alignment.params.chip": "-t 8 -q 20 -b",
  "aligner.bs": "bsmap",
  "alignment.params.bs": "-g 3 -v 0.2",
  "plotRepTree.meth.minCpGs": 2,
  "plotRepTree.meth.minReads": 100
}

You can load them using

loadConfig("config.json")

Alternatively or in addition, you can specify individual options from within R:

setConfigElement("species", "human")

To see a description of all options you can specify:

?setConfigElement

Running the analysis (R)

For running the enire analysis you need to specify the output directory (anaDir in the following code) and the prepared file annotation table fileTable.tsv in the following code):

anaDir <- "repeatAnalysis"
runAnalysis(anaDir, fileTable="fileTable.tsv")

If your analysis stops at some point, you can resume the analysis again using runAnalysis and specifying the same output directory as before (assuming it still exists).

Running the analysis (command line)

You can also run the analysis comfortable from the command line. To do so, download theepiRepeatR.R file from our github repository (https://github.com/MPIIComputationalEpigenetics/epiRepeatR/blob/master/inst/extdata/epiRepeatR.R) and then execute it using Rscript:

Rscript epiRepeatR.R --analysisDir $ANADIR --fileTable fileTable.tsv --configFile config.json

or in short form

Rscript epiRepeatR.R -a $ANADIR -f fileTable.tsv -c config.json

You can also omit the config file and manually set some of the options from the command line. However, note that currently only a limited set of options is supported from the command line.

Rscript epiRepeatR.R -a $ANADIR -f fileTable.tsv --referenceFasta Homo_sapiens_all.fa --numProcesses 4

---

author: Fabian Müller <[e-mail]>

MPIIComputationalEpigenetics/epiRepeatR documentation built on March 22, 2021, 11:09 p.m.