Process Hi-C pairs with pairtools
pairtools is a simple and fast command-line framework to process sequencing
data from a Hi-C experiment.
pairtools process pair-end sequence alignments and perform the following
- detect ligation junctions (a.k.a. Hi-C pairs) in aligned paired-end sequences of Hi-C DNA molecules
- sort .pairs files for downstream analyses
- detect, tag and remove PCR/optical duplicates
- generate extensive statistics of Hi-C datasets
- select Hi-C pairs given flexibly defined criteria
- restore .sam alignments from Hi-C pairs
- annotate restriction digestion sites
- get the mutated positions in Hi-C pairs
To get started:
pairtools produce and operate on tab-separated files compliant with the
format defined by the 4D Nucleome Consortium. All
pairtools properly manage file headers and keep track of the data
pairtools define the .pairsam format, an extension of .pairs that includes the SAM alignments
of a sequenced Hi-C molecule. .pairsam complies with the .pairs format, and can be processed by any tool that
operates on .pairs files.
pairtools produces a set of additional extra columns, which describe properties of alignments, phase, mutations, restriction and complex walks.
The full list of possible extra columns is provided in the
pairtools format specification.
- Python 3.x
- Python packages
- Command-line utilities
sort(the Unix version),
samtools. If available,
pairtoolscan compress outputs with
For the full list of recommended versions, see requirements in the the GitHub repo.
We highly recommend using the
conda package manager to install
pairtools together with all its dependencies. To get it, you can either install the full Anaconda Python distribution or just the standalone conda package manager.
conda, you can install
pairtools and all of its dependencies from the bioconda channel.
$ conda install -c conda-forge -c bioconda pairtools
Alternatively, install non-Python dependencies and
pairtools with Python-only dependencies from PyPI using pip:
$ pip install numpy pysam cython $ pip install pairtools
Setup a new test folder and download a small Hi-C dataset mapped to sacCer3 genome:
$ mkdir /tmp/test-pairtools $ cd /tmp/test-pairtools $ wget https://github.com/open2c/distiller-test-data/raw/master/bam/MATalpha_R1.bam
Additionally, we will need a .chromsizes file, a TAB-separated plain text table describing the names, sizes and the order of chromosomes in the genome assembly used during mapping:
$ wget https://raw.githubusercontent.com/open2c/distiller-test-data/master/genome/sacCer3.reduced.chrom.sizes
pairtools parse, we can convert paired-end sequence alignments stored in .sam/.bam format into .pairs, a TAB-separated table of Hi-C ligation junctions:
$ pairtools parse -c sacCer3.reduced.chrom.sizes -o MATalpha_R1.pairs.gz --drop-sam MATalpha_R1.bam
Inspect the resulting table:
$ less MATalpha_R1.pairs.gz
- We provide a simple working example of a mapping bash pipeline in /examples/.
distiller is a powerful
Hi-C data analysis workflow, based on
parse: read .sam/.bam files produced by bwa and form Hi-C pairs
- form Hi-C pairs by reporting the outer-most mapped positions and the strand on the either side of each molecule;
- report unmapped/multimapped (ambiguous alignments)/chimeric alignments as chromosome "!", position 0, strand "-";
- perform upper-triangular flipping of the sides of Hi-C molecules such that the first side has a lower sorting index than the second side;
- form hybrid pairsam output, where each line contains all available data for one Hi-C molecule (outer-most mapped positions on the either side, read ID, pair type, and .sam entries for each alignment);
- report .sam tags or mutations of the alignments;
- print the .sam header as #-comment lines at the start of the file.
parse2: read .sam/.bam files with long paired-and or single-end reads and form Hi-C pairs from complex walks
- identify and rescue chrimeric alignments produced by singly-ligated Hi-C molecules with a sequenced ligation junction on one of the sides;
- annotate chimeric alignments by restriction fragments and report true junctions and hops (One-Read-Based Interactions Annotation, ORBITA);
- perform intra-molecule deduplication of paired-end data when one side reads through the DNA on the other side of the read;
- report index of the pair in the complex walk;
- make combinatorial expansion of pairs produced from the same walk;
sort: sort pairs files (the lexicographic order for chromosomes, the numeric order for the positions, the lexicographic order for pair types).
merge: merge sorted .pairs files
- merge sort .pairs;
- combine the .pairs headers from all input files;
- check that each .pairs file was mapped to the same reference genome index (by checking the identity of the @SQ sam header lines).
select: select pairs according to specified criteria
- select pairs entries according to the provided condition. A programmable interface allows for arbitrarily complex queries on specific pair types, chromosomes, positions, strands, read IDs (including matches to a wildcard/regexp/list).
- optionally print the non-matching entries into a separate file.
dedup: remove PCR duplicates from a sorted triu-flipped .pairs file
- remove PCR duplicates by finding pairs of entries with both sides mapped to similar genomic locations (+/- N bp);
- optionally output the PCR duplicate entries into a separate file;
- detect optical duplicates from the original Illumina read ids;
- apply filtering by various properties of pairs (MAPQ; orientation; distance) together with deduplication;
- output yaml or convenient tsv deduplication stats into text file.
- NOTE: in order to remove all PCR duplicates, the input must contain *all* mapped read pairs from a single experimental replicate;
maskasdup: mark all pairs in a pairsam as Hi-C duplicates
- change the field pair_type to DD;
- change the pair_type tag (Yt:Z:) for all sam alignments;
- set the PCR duplicate binary flag for all sam alignments (0x400).
split: split a .pairsam file into .pairs and .sam.
flip: flip pairs to get an upper-triangular matrix
header: manipulate the .pairs/.pairsam header
- generate new header for headerless .pairs file
- transfer header from one .pairs file to another
- set column names for the .pairs file
- validate that the header corresponds to the information stored in .pairs file
stats: calculate various statistics of .pairs files
restrict: identify the span of the restriction fragment forming a Hi-C junction
phase: phase pairs mapped to a diploid genome
Pull requests are welcome.
For development, clone and install in "editable" (i.e. development) mode with the
-e option. This way you can also pull changes on the fly.
$ git clone https://github.com/open2c/pairtools.git $ cd pairtools $ pip install -e .
Open2C*, Nezar Abdennur, Geoffrey Fudenberg, Ilya M. Flyamer, Aleksandra A. Galitsyna*, Anton Goloborodko*, Maxim Imakaev, Sergey V. Venev. "Pairtools: from sequencing data to chromosome contacts" bioRxiv, February 13, 2023. ; doi: https://doi.org/10.1101/2023.02.13.528389