Skip to main content

CD-HIT cluster parser

Project description

cdhit-parser

Python package Conda downloads pipy

CD-HIT file reader.

Read CD-HIT .clstr file

Basic usage

input = "cluster.fa.clstr"
for cluster in read_cdhit(input):
    print(f"{cluster.name} refSequence={cluster.refname} size={len(cluster)}")

    for member in cluster.sequences:
        print(f" {member.name} ({member.length}) identity={member.identity}% {'(Reference sequence)' if member.is_ref else ''}")

Load all clusters in to a list:

# Load all clusters to a list
clusters = read_cdhit(input).read_items()

Read FASTA file

if os.path.exists(fileName):
    for seq in cdhit_reader.read_fasta(fileName, line_len=60):
        print(seq) # will be wrapped at 60 chars per line, use 0 to disable wrapping
        
        # to access individual attributes:
        # print(">" + seq.name + " " + seq.comment + "\n" + seq.sequence)

Install

pip install cdhit-reader

or via Miniconda, which will also install cd-hit

conda install -c bioconda -c conda-forge cdhit-reader

Demo applications

Cluster stats

The module ships a demo program called cdhit-reader.py.

cdhit-parser -h

Compare two fasta files

:warning: This requires cd-hit installed and available in the system path.

cdhit-compare allows to compare two fasta files and print the sequences that are in common, those which are only present in one of the files or those which are redundant.

cdhit-compare --help

Example:

cdhit-compare data/input1.faa data/input2.faa  --id 0.99

will produce:

input1  BJJOHBJ_00007
input2  BJJOHBJ_00007
input2  BJJOHBJ_00002
both    BJJOHBJ_00003:BJJOHBJ_00003
both    BJJOHBJ_00005:BJJOHBJ_00005
both    BJJOHBJ_00004:BJJOHBJ_00004
multi   input1#IBJJOHBJ_00006,input1#BBJJOHBJ_000B6,input1#CBJJOHBJ_000C6,input2#IBJJOHBJ_00006,input2#BBJJOHBJ_000B6,input2#CBJJOHBJ_000C6
dupl_input1     BJJOHBJ_00001:BJJOHBJ_000F

where records starting with file1 or file2 are only present in one of the files, records starting with both are present in both files (one per file), records starting with dupl are duplicates (two in one of the files), and records starting with multi are present multiple times in at least one of the datasets.

Author

License

This project is licensed under the MIT License.

Acknowledgments

This module was based on fasta_reader by Danilo Horta

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

cdhit-reader-0.1.1.tar.gz (12.6 kB view details)

Uploaded Source

Built Distribution

cdhit_reader-0.1.1-py3-none-any.whl (13.8 kB view details)

Uploaded Python 3

File details

Details for the file cdhit-reader-0.1.1.tar.gz.

File metadata

  • Download URL: cdhit-reader-0.1.1.tar.gz
  • Upload date:
  • Size: 12.6 kB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.15

File hashes

Hashes for cdhit-reader-0.1.1.tar.gz
Algorithm Hash digest
SHA256 8b57ed77cbad877b28d374324cb6876c3cc8c55ce96add4d97baf939d4799b42
MD5 05739464a29b214cd025dd27225b26a6
BLAKE2b-256 50b3af3208de1166f6529e049112c7f0e3c9d13d01968050badc985f79d72d95

See more details on using hashes here.

File details

Details for the file cdhit_reader-0.1.1-py3-none-any.whl.

File metadata

  • Download URL: cdhit_reader-0.1.1-py3-none-any.whl
  • Upload date:
  • Size: 13.8 kB
  • Tags: Python 3
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.1 CPython/3.9.15

File hashes

Hashes for cdhit_reader-0.1.1-py3-none-any.whl
Algorithm Hash digest
SHA256 361956326e84ad9d329f2d6cc2d6955f4dba26a925921b4fdacff04d806489d7
MD5 cc2061cdfefd4b82295434e109f60f91
BLAKE2b-256 6a257a153ff5b3aa10189088b64fcc634d7fe5b7d7c9da7f46bae9fd54942e97

See more details on using hashes here.

Supported by

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