minimap2 PAF file reader
Project description
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.
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