readpaf 0.0.1a1

minimap2 PAF file reader

readpaf

Scripts for reading minimap2 PAF files

Installation

readpaf is contained in a single module so can be installed via PyPI:

pip install readpaf

inlcuding pandas:

pip install readpaf[pandas]

Or readpaf.py can be directly downloaded like so

using cURL

curl -O https://raw.githubusercontent.com/alexomics/read-paf/main/readpaf.py

or wget

wget https://raw.githubusercontent.com/alexomics/read-paf/main/readpaf.py

Usage

The following script demonstrates how minimap2 output can be piped into read-paf

from readpaf import parse_paf
from sys import stdin

for record in parse_paf(stdin):
    print(record.query_name, record.target_name)

read-paf can also generate a pandas DataFrame:

from readpaf import parse_paf

with open("test.paf", "r") as handle:
    df = parse_paf(handle, dataframe=True)

Functions

read-paf has a single user function

parse_paf

parse_paf(file_like=file_handle, fields=list, dataframe=bool)

Parameters:

• file_like: A file like object, such as sys.stdin, a file handle from open or io.StringIO objects
• fields: A list of 13 field names to use for the PAF file, default:

  "query_name", "query_length", "query_start", "query_end", "strand",
  "target_name", "target_length", "target_start", "target_end",
  "residue_matches", "alignment_block_length", "mapping_quality", "tags"
  

  These are based on the PAF specification.
• dataframe: bool, if True, return a pandas.DataFrame with the tags expanded into separate Series

If used as an iterator, then each object returned is a named tuple representing a single line in the PAF file. Each named tuple has field names as specified by the fields parameter. The SAM-like tags are converted into their correct types and stored in a dictionary.

If used to generate a pandas DataFrame, then each row represents a line in the PAF file and the SAM-like tags are expanded into individual series.