Skip to content

wg-blimp: an end-to-end analysis pipeline for whole genome bisulfite sequencing data

License

Notifications You must be signed in to change notification settings

MarWoes/wg-blimp

Repository files navigation

wg-blimp (Whole Genome BisuLfIte sequencing Methylation analysis Pipeline) can be utilised to analyse WGBS data. It performs alignment, qc, methylation calling, DMR calling, segmentation and annotation using a multitude of tools. First time using wg-blimp? We recommend having a look at our step-by-step guide.

Requirements

To run wg-blimp you need a UNIX environment that contains a Bioconda setup.

Installation

Recommended

It is advised to install wg-blimp through Bioconda. It is also recommended to install wg-blimp in a fresh environment, as it has many dependencies that may conflict with other packages, for this you can use:

conda create -n wg-blimp wg-blimp python=3.6

The requirement python=3.6 is currently necessary because of otherwise slow conda dependency solving.

From source

You can also install wg-blimp from source using

python setup.py install

Using this installation method requires you to make sure all external tools are installed (such as bwa-meth).

Running wg-blimp

WGBS pipeline

wg-blimp is a cli wrapper for the WGBS pipeline implemented using Snakemake. In general, a pipeline config us fed to the Snakemake workflow and the corresponding tools are called. However, wg-blimp also provides some commands to ease creation of config files, or working without config files altogether.

The command wg-blimp run-snakemake will run the pipeline with its default parameters. Make sure to set the --cores and --genome-build options appropriately. This command will also internally create a config.yaml file containing all parameters used for the analysis.

However, in case the default configurations are not sufficient, users can provide their own configurations. The commands wg-blimp create-config and wg-blimp run-snakemake-from-config can be used for this purpose.

wg-blimp will attempt to match .fastq files to sample names by searching for sample names in .fastq file names. By default Illumina naming conventions are expected, e.g. for a samples test1 the .fastq files should be named as follows:

test1_L001_R1_001.fastq.gz
test1_L001_R1_002.fastq.gz
test1_L001_R2_001.fastq.gz
test1_L001_R2_002.fastq.gz
test1_L002_R1_001.fastq.gz
test1_L002_R1_002.fastq.gz
test1_L002_R2_001.fastq.gz
test1_L002_R2_002.fastq.gz

If names derive from this pattern, users can adjust the regular expression to match in the config file's rawsuffixregex entry.

The folder structure created by wg-blimp run-snakemake will look as follows:

  • alignment - contains all bam/bai files
  • dmr - contains dmr files by different callers
  • logs - each pipeline step deposits its logs here
  • methylation - methylation bedgraph files
  • qc - multiqc and other qc related files
  • raw - text files describing which fastq files have been used for each sample
  • segmentation - methylome segments (UMRs/LMRs/PMDs) as computed by MethylSeekR
  • config.yaml - configuration file used for the analysis

It is recommended to check the raw folder if all samples contain the correct raw fastq source files.

Shiny GUI

You can use the command wg-blimp run-shiny to load one or more project config files into a shiny GUI for easier access.

Example

Some example .fastqcan be found on Sciebo. You can use the command

wg-blimp run-snakemake <folder-with-fastqs> <reference.fa> simulated1,simulated2 simulated3,simulated4 <output-folder>

Please not that the pipeline commands also allow a --use-sample-files option so sample groups can be loaded from text files instead of comma separates files.

Config parameters

The following entries are used for running the Snakemake pipeline and may be specified in the config.yaml files:

Key Value
annotation_allowed_biotypes Only genes with this biotype will be annotated in the DMR table
annotation_min_mapq When annotating coverage, only use reads with a minimum mapping quality
bsseq_local_correct Use local correction for bsseq DMR calling. Usually, setting this to FALSE will increase the number of calls.
cgi_annotation_file Gzipped csv file used for cg island annotation.
computing_threads Number of processors a single job is allowed to use. Remember to use --cores parameter for Snakemake.
dmr_tools Tools to use for DMR calling. Available: bsseq, camel, metilene
gene_annotation_file File used for genetic annotation.
group1 Samples in first group for DMR analysis
group2 Samples in second group for DMR analysis
io_threads IO intensive tools virtually reserve this many cores (while actually using only one) to reduce file system IO load.
methylation_rate_on_chromosomes Compute methylation rates for these chromosome during qc
methylseekr_cgi_genome Reference genome to use for MethylSeekR CGI queries.
methylseekr_fdr_cutoff FDR cutoff for MethylSeekR segmentation.
methylseekr_methylation_cutoff Methylation cutoff for MethylSeekR segmentation.
methylseekr_pmd_chromosome Chromosome to compute MethylSeekR alpha values for.
min_cov Minimum average coverage for methylation calling
min_cpg Minimum number of CpGs in a DMR to be called
min_diff Minimum average difference between the two groups for DMR calling
output_dir Directory containing all files created by the pipeline
promoter_tss_distances Distance interval around TSS's to be recognized as promoters in DMR annotation.
qualimap_memory_gb Gigabytes of RAM to allocate for Qualimap. If samples are too large, this must be increased to prevent crashes.
rawdir Directory containing .fastq files
rawsuffixregex The regular expressions to match for paired reads. By default, Illumina naming conventions are accepted.
ref .fasta reference file
repeat_masker_annotation_file File containing repeat masker annotation
repeat_masker_links Repeat masker files are relatively big and are only downloaded on demand from the links specified here.
samples All samples (usually concatenation of group1 and group2)
target_files Files to be generated by the Snakemake workflow
transcript_start_site_file File to read transcription start sites from (for DMR annotation)

Reporting errors / Requesting features

If anything goes wrong using wg-blimp or any features are missing, feel free to open an issue or to contact Marius Wöste ( mar.w@wwu.de )

About

wg-blimp: an end-to-end analysis pipeline for whole genome bisulfite sequencing data

Resources

License

Stars

Watchers

Forks

Packages

No packages published