Skip to main content

Some tools I find useful for working with Ig receptor sequences

Project description

receptor_utils

Some tools I find useful for working with Ig receptor sequences.

Installation

pip install receptor-utils

The module requires Biopython.

Overview

Please refer to the files themselves for slightly more detailed documentation.

simple_bio_seq

Contains some convenience functions that are backed by BioPython but simplified for my use case. It uses the following approach to keep things simple (at the expense of some flexibility/scalability):

  • store sequences as strings, use dicts for collections
  • convert sequences to upper case on input
  • coerce iterators into lists for ease of debugging
from receptor_utils import simple_bio_seq as simple
seqs = simple.read_fasta('seqfile.fasta')  # read sequences into a dict with names as keys
seq = simple.read_single_fasta('seqfile.fasta')  # reads the first or only sequence into a string
seq = simple.reverse_complement(seq)

See the file for other functions.

novel_allele_name

Contains the function name_novel(), which will generate a name for a 'previously undocumented' allele, given its sequence. The name will consist of the name of the nearest allele in a reference set provided to the function, suffixed by the SNPs that differentiate it, for example:

IGHV1-69*01_a29g_c113t

Numbering of V-sequences uses the IMGT alignment. The naming convention follows that used by Tigger and VDJbase.

number_ighv

Contains various functions for working with V-sequences according to the IMGT numbering scheme. The most useful is gap_sequence() which will gap the provided V-sequence by using the closest sequence in a reference set as a template.

Example scripts

These may be useful in their own right, but also show how to use some of the functions mentioned above. Once the package is installed, you should be able to run these at the command line without the .py extension, for example type

$ extract_refs --help

for help

extract_refs

A script which uses simple_bio_seq to extract files for particular loci and species from an IMGT reference file.

gap_inferred

A script which will gap a set of sequences listed in a FASTA file, using the closest sequences discovered from a reference set. The script will do its best to warn of issues with the reference sequences and with the gapped sequences it provides: please use the warnings to check that things are ok.

Sequences to be gapped are assumed to be complete at the 5' end. If necessary they should be gapped with dots at the 5' end, so that the first nucleotide is at the correct position in the full-length sequence (in exactly the same way that IMGT puts dots at the start of a reference sequence that is incomplete at the 5' end)

identical_seqs

A script which uses simple_bio_seq to list identical sequences and sub-sequences in a fasta file.

make_igblast_ndm

A script which uses a set of IMGT-gapped V-sequences to create the ndm file required by IgBLAST for a custom organism

annotate_j

Given a set of J sequences, identify the correct frame and location of the CDR3 end, by searching for the GxG motif.

rev_comp

Return the reverse-complement of the specified nucleotide sequence.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

receptor_utils-0.0.17.tar.gz (14.4 kB view details)

Uploaded Source

Built Distribution

If you're not sure about the file name format, learn more about wheel file names.

receptor_utils-0.0.17-py3-none-any.whl (17.8 kB view details)

Uploaded Python 3

File details

Details for the file receptor_utils-0.0.17.tar.gz.

File metadata

  • Download URL: receptor_utils-0.0.17.tar.gz
  • Upload date:
  • Size: 14.4 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7

File hashes

Hashes for receptor_utils-0.0.17.tar.gz
Algorithm Hash digest
SHA256 485a47a09589be8b40516365ff3d2e3ba2e00765adec8a06cd65880513d050e4
MD5 ebef27d58fa8a719e44ab2eaec851a08
BLAKE2b-256 cc03289a5af219f0919904f19133f0e233d558fbe4734762de1dc2d70b87a221

See more details on using hashes here.

File details

Details for the file receptor_utils-0.0.17-py3-none-any.whl.

File metadata

  • Download URL: receptor_utils-0.0.17-py3-none-any.whl
  • Upload date:
  • Size: 17.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.7.1 importlib_metadata/4.10.0 pkginfo/1.8.2 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.7

File hashes

Hashes for receptor_utils-0.0.17-py3-none-any.whl
Algorithm Hash digest
SHA256 a463c0f224399c923f42a578298a2618392ae088003f20ef1823704519b1bb67
MD5 6bb49a1e4e2c99aeb8a89100d690b803
BLAKE2b-256 f9ddc687226bb68638bb5979e6aa18001a7804c7ca73b012e5cffef8ea2a2104

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Depot Continuous Integration Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page