=======================
Minimap2 Python Binding
=======================
`Minimap2 <https://github.com/lh3/minimap2>` is a fast and accurate pairwise
aligner for genomic and transcribed nucleotide sequences. This module wraps
minimap2 and provides a convenient interface to calling minimap2 in Python.
Installation
------------
The minimap2 model can be installed directly with:
.. code:: shell
git clone https://github.com/lh3/minimap2
cd minimap2
python setup.py install
or with pip:
.. code:: shell
pip install --user minimap2
Usage
-----
The following Python program shows the key functionality of this module:
.. code:: python
import minimap2 as mm
a = mm.Aligner("test/MT-human.fa")
if not a: raise Exception("ERROR: failed to load/build index")
for hit in a.map("GGTTAAATACAGACCAAGAGCCTTCAAAGCCCTCAGTAAGTTGCAATACTTAATTTCTGT"):
print("{}\t{}\t{}\t{}".format(hit.ctg, hit.r_st, hit.r_en, hit.cigar_str))
It builds an index from the specified sequence file (or loads an index if a
pre-built index is supplied), aligns a sequence against it, traverses each hit
and prints them out.
APIs
----
Class minimap2.Aligner
~~~~~~~~~~~~~~~~~~~~~~
.. code:: python
Aligner(fn_idx_in, preset=None, ...)
Arguments:
* `fn_idx_in`: index or sequence file name. Minimap2 automatically tests the
file type. If a sequence file is provided, minimap2 builds an index. The
sequence file can be optionally gzip'd.
* `preset`: minimap2 preset. Currently, minimap2 supports the following
presets: `sr` for single-end short reads; `map-pb` for PacBio
read-to-reference mapping; `map-ont` for Oxford Nanopore read mapping;
`splice` for long-read spliced alignment; `asm5` for assembly-to-assembly
alignment; `asm10` for full genome alignment of closely related species. Note
that the Python module does not support all-vs-all read overlapping.
* `k`: k-mer length, no larger than 28
* `w`: minimizer window size, no larger than 255
* `min_cnt`: mininum number of minimizers on a chain
* `min_chain_score`: minimum chaing score
* `bw`: chaining and alignment band width
* `best_n`: max number of alignments to return
* `n_threads`: number of indexing threads; 3 by default
* `fn_idx_out`: name of file to which the index is written
.. code:: python
map(query_seq)
This methods maps `query_seq` against the index. It *yields* a generator,
generating a series of `Alignment` objects.
Class minimap2.Alignment
~~~~~~~~~~~~~~~~~~~~~~~~
This class has the following properties:
* `ctg`: name of the reference sequence the query is mapped to
* `ctg_len`: total length of the reference sequence
* `r_st` and `r_en`: start and end positions on the reference
* `q_st` and `q_en`: start and end positions on the query
* `strand`: +1 if on the forward strand; -1 if on the reverse strand
* `mapq`: mapping quality
* `NM`: number of mismatches and gaps in the alignment
* `blen`: length of the alignment, including both alignment matches and gaps
* `trans_strand`: transcript strand. +1 if on the forward strand; -1 if on the
reverse strand; 0 if unknown
* `is_primary`: if the alignment is primary (typically the best and the first
to generate)
* `cigar_str`: CIGAR string
* `cigar`: CIGAR returned as an array of shape `(n_cigar,2)`. The two numbers
give the length and the operator of each CIGAR operation.
An Alignment object can be converted to a string in the following format:
::
q_st q_en strand ctg ctg_len r_st r_en blen-NM blen mapq cg:Z:cigar_str
ddc2c6f279