damidseq_pipeline

An automated pipeline for processing DamID sequencing datasets

Introduction

Processing DamID-seq data involves extending single-end reads, aligning the reads to the genome and determining the coverage, similar to processing regular ChIP-seq datasets. However, as DamID data is represented as a log2 ratio of (Dam-fusion/Dam), normalisation of the sample and Dam-only control is necessary and adding pseudocounts to mitigate the effect of background counts is highly recommended.

damidseq_pipeline is a single script that automatically handles sequence alignment, read extension, binned counts, normalisation, pseudocount addition and final ratio file generation. The script uses FASTQ or BAM files as input, and outputs the final log2 ratio files in bedGraph (or optionally GFF) format.

The output ratio files can easily be converted to TDF for viewing in IGV using igvtools. The files can be processed for peak calling using find_peaks or, if using RNA pol II DamID, transcribed genes can be determined using polii.gene.call.

Citation

If you find this software useful, please cite:

Marshall OJ and Brand AH. (2015) damidseq_pipeline: an automated pipeline for processing DamID sequencing datasets. Bioinformatics. Oct 15;31(20):3371-3. doi: 10.1093/bioinformatics/btv386. (pubmed; full text, open access)

Download

Important: if using a version of the pipeline less than v1.3, please update as older versions did not correctly account for reads on the minus strand during read extension. The difference in the final output files is minimal (the Spearman's correlation between files generated with v1.2.6 or less or v1.3 is >0.95) but files generated by the new method should be more accurate.

Download the latest version of the pipeline script and associated files:

Prebuilt GATC fragment files used by the script are available for the following genomes:

Requirements

Installation

  1. Extract the pipeline script archive, make the damid_pipeline file executable and place it in your path
  2. Install Bowtie 2
  3. Obtain Bowtie 2 indices provided by Bowtie 2 or Illumina's iGenome

    Alternatively, build the Bowtie 2 index files manually:

    1. Download the latest FASTA genome primary_assembly (or toplevel) file from Ensembl e.g. the current release for Mus musculus

      (alternatively, for Drosophila, download from the Flybase FTP site (ftp://ftp.flybase.net/releases/current/) e.g. ftp://ftp.flybase.net/releases/FB2014_03/dmel_r5.57/fasta/dmel-all-chromosome-r5.57.fasta.gz )

    2. Extract the .gz file
    3. Run bowtie2-build in the directory containing the extracted .fasta file. For the examples above:

      bowtie2-build Mus_musculus.GRCm38.dna.primary_assembly.fa GRCm38
      bowtie2-build dmel-all-chromosome-r5.57.fasta dmel_r5.57
      
  4. Install SAMtools
  5. Download a pre-built GATC fragment file for

    Alternatively build your own:

    1. Download the FASTA genome sequence, as in step 3 above (no need to extract the gzipped files)
    2. Run the provided gatc.track.maker.pl script on the fasta sequence, e.g.:

      perl gatc.track.maker.pl --name=dmel_r5.57 dmel-all-chromosome-r5.57.fasta
      

Running the script the first time

In order to run correctly, the script needs to know the locations of two paths, specified using the following command-line options:

  1. The directory and basename of the bowtie2 index files (obtained or built in step 3 above) (specified with the --bowtie2_genome_dir option) e.g. in the example above, use

    --bowtie2_genome_dir=[path_to_.bt2_files]/dmel_r5.57
    
  2. The GATC fragment .gff file (downloaded from the pre-built files listed in step 5, or built following the instructions above) (specified with the --gatc_frag_file option)

In order to setup the pipeline to process the D. melanogaster genome, for example, the first-run command would be:

damidseq_pipeline --gatc_frag_file=path/to/Dmel_r5.57.GATC.gff.gz --bowtie2_genome_dir=path/to/dmel_r5.57/dmel_r.5.57

If these paths do not already exist and the script is run with these options and correct values, the paths will be saved for all future runs unless overridden on the command-line.

(To clear all user-saved values, run the script with the --reset_defaults option.)

Running the script

Run the script in a directory with sequencing files in FASTQ or BAM format. The default behaviour is to process all files in FASTQ format, and if none are found, all files in BAM format. Alternatively, individual files may be specified on the command line if the user does not wish to process all available files present in the directory (for example, if the sequencing lane contained multiple replicates).

The script will by default determine sample names from the file names, and expects a single filename to start with "Dam" in order to automatically assign the Dam-only control.

To see all available options, run the script with --help command-line option:

damidseq_pipeline --help

This will give you a list of adjustable parameters and their default and current values if applicable. We recommend keeping these at the default value in most cases; however, these can be modified on the command-line with --option=value (no spaces).

To save modified values for all future runs, run the script with the parameter you wish to change together with the --save_defaults command-line option:

damidseq_pipeline --save_defaults

If bowtie2 and samtools are not in your path, you can specify these on the command-line also.

Output and downstream data processing

The final output will be a single ratio file: Sample-vs-DAM.gatc.bedgraph. The .gatc.bedgraph file represents the data at GATC fragment resolution (based on the reference genome) and should be used for all subsequent analysis.

The bedGraph format is used by default. The pipeline script can output the final ratio files in GFF format instead if the --output_format=gff command-line switch is used.

Visualising the DNA binding profiles

The bedgraph output file can be can be converted to .tdf format via igvtools, either using the graphical interface provided by IGV or via the command-line. A legacy gff2tdf.pl script is also provided for converting GFF files (the default output file format prior to v1.4) to TDF.

Calling significant peaks from the data

The find_peaks software will process the output .gatc.bedgraph ratio file and call significant peaks present in the dataset. Please see the find_peaks page for more details.

Calling transcribed genes from RNA pol II datasets

The polii.gene.call Rscript will call transcribed genes (i.e. gene bodies with significantly enriched pol II occupancy) from the output .gatc.bedgraph file. Please see the polii.gene.call page for more details.

Other useful scripts and utilities

A collection of useful R and Perl scripts for comparing and analysing DamID-seq data is maintained at [http://github.com/owenjm/damid_misc].

Working with multiple genomes

If the user expects to process data from multiple genomes, separate genome specifications can be saved by using the --save_defaults=[name] along with the --bowtie2_genome_dir and --gatc_frag_file options (and any other custom options that the user wishes to set as default for this genome, e.g. the bin width). For e.g.:

damidseq_pipeline --save_defaults=fly --gatc_frag_file=path/to/Dmel_r5.57.GATC.gff.gz --bowtie2_genome_dir=path/to/dmel_r5.57/dmel_r.5.57
damidseq_pipeline --save_defaults=mouse --bins=500 --gatc_frag_file=path/to/MmGRCm38.GATC.gff.gz --bowtie2_genome_dir=path/to/Mm_GRCm38/GRCm38

Once set up, different genome definitions can be quickly loaded using the --load_defaults=[name] option, e.g.:

damidseq_pipeline --load_defaults=fly

All currently saved genome definitions can be listed using --load_defaults=list.

Processing FASTQ files with adaptor codes

The damidseq_pipeline will attempt to automatically determine the sample name from the filenames provided.

Some sequencing facilities, however, may provide only adaptor index IDs rather than sample names. If sequencing filenames are provided with index IDs rather than names, a file "index.txt" in the working directory can be provided with the format of [index] [sample_name], eg:

A6 Dam
A12 polII 

where A6 is the sequencing adaptor index. The sample name cannot contain spaces and there has to be one (and only one) sample called "Dam"; the adaptor index must to be referenced in the fastq filename (e.g. for "A6", either "Index6" or "A006" are expected in the filename). Please see the provided example for an illustration of the index.txt file format and matching file names.

Example dataset

An example set of two small (3000 reads each) fastq.gz files and an index.txt file are provided in the zip archive (as "example.zip"), or you can download these separately. Running the pipeline script on these files should successfully produce a polII-vs-Dam.gatc.bedgraph ratio file as output.