triform2

ChIP-Seq caller for transcription factor binding sites.

Very alpha edition, so please post questions, issues, docrequests etc at the triform2 google groups forum.

Install

Clone repo and run with python triform2.py -h

Papers

• The Triform algorithm: improved sensitivity and specificity in ChIP-Seq peak finding
• ChIP analysis unravels an exceptionally wide distribution of DNA binding sites for the NtcA transcription factor in a heterocyst-forming cyanobacterium

CLI

usage: triform2.py [-h] --treatment TREATMENT [TREATMENT ...] --control
                   CONTROL [CONTROL ...] [--number-cores NUMBER_CORES]
                   [--genome GENOME] [--bedgraph BEDGRAPH] [--max-p MAX_P]
                   [--min-shift MIN_SHIFT] [--min-width MIN_WIDTH]
                   [--read-width READ_WIDTH] [--flank-distance FLANK_DISTANCE]
                   [--min-enrichment MIN_ENRICHMENT] [--version]

Improved sensitivity, specificity and control of false discovery rates in
ChIP-Seq peak finding. (Visit github.com/endrebak/triform for examples and
help.)

optional arguments:
  -h, --help            show this help message and exit
  --treatment TREATMENT [TREATMENT ...], -t TREATMENT [TREATMENT ...]
                        Treatment (pull-down) file(s) in
                        bam/bed/bed.gz/bed.bz2 format.
  --control CONTROL [CONTROL ...], -c CONTROL [CONTROL ...]
                        Control (input) file(s) in bam/bed/bed.gz/bed.bz2
                        format.
  --number-cores NUMBER_CORES, -cpu NUMBER_CORES
                        Number of cpus to use. Can use at most one per
                        chromosome. Default: 1.
  --genome GENOME, -g GENOME
                        Genome version to use.
  --bedgraph BEDGRAPH, -b BEDGRAPH
                        Path to write bedgraph file to, if desired.
  --max-p MAX_P, -mp MAX_P
                        Used to calculate minimum upper-tail z-value (default
                        corresponds to standard normal p = 0.1)
  --min-shift MIN_SHIFT, -ms MIN_SHIFT
                        Minimum inter-strand shift (lag) between peak coverage
                        distributions (default 10 bp).
  --min-width MIN_WIDTH, -mw MIN_WIDTH
                        Minimum number of bp (peak width) in peak-like region
                        (default 10 bp).
  --read-width READ_WIDTH, -rw READ_WIDTH
                        Read width w, symmetrically extended to a fixed value.
                        Must be larger than the flank size. Default: 100 bp.
  --flank-distance FLANK_DISTANCE, -fd FLANK_DISTANCE
                        Fixed spacing between central and flanking locations
                        (must be > w). Default: 150 bp.
  --min-enrichment MIN_ENRICHMENT, -mr MIN_ENRICHMENT
                        Minimum local enrichment ratio (default 3/8 quantile
                        of the enrichment ratio)
  --version, -v         show program's version number and exit

TODO

• check that there are type 1, 2, 3 peaks before trying to exclude them
• only require a certain percentage of ChIP files to show a peak?
• ensure chromosomes operated on in correct order
• merge type 2/3 peaks
• create setup.py
• add cl-arg for merge distance
• add to travis ci
• add to bioconda
• create wrapper for asciigenome to print peaks
• create galaxy wrapper
• add to coveralls
• also make bedgraph of peaks before merging on strand? (ask advisors if this will be valuable)

Done

• Make possible to use without input data
• Suite of unit-tests
• Implemented FDR calculations
• Take input/chip files as command line arguments (easy)
• Do not require input files to follow a naming convention (easy)
• Do not use temp-files, keep data in memory (to speed up the algorithm and avoid file paths in the code) (medium)
• Run chromosomes in parallel (unknown difficulty)
• Accept an arbitrary number of chip and input-files (hard?)