Bioinformatics File Operations Toolkit.
Project description
Introduction
BioFileKit: Designed to provide bioinformatics researchers and developers with a powerful, user-friendly and extensible Python toolkit, it focuses on simplifying the reading, writing, conversion, parsing and basic operations of various biological data file formats. Say goodbye to reinventing the wheel and the cumbersome format analysis, and focus on your scientific discoveries!
Install
pip install biofile_kit
Usage example
Generate random nucleotide sequences
fasta_tools random_nucl -n seq1,seq2 -l 1000,1200
>seq1 length=1000
CGCCAGGCCTGCCCTGCGACGGAGGTTCCCCGTATGACTGCCCTATATCATTCCTGCTAAACTCAATCCACAAGATCAATTCACTCCGGGGAACAACTGCCACTAGAAACCGTAGGTTACCATCAATAGTTCCCCACTTGGAGGAAGAAGTCTTTGAAGCAGGTTGTCATCCAGCATTCTTTCTAAACGTCATTGGACATAGGGGTAAGCTCATATCCTCTCCCAACCATTCAGAAGTCCATGACCATGTCCGGTGCAAATTTGAAAGTCATGATGGTGAGGGAGCAAGAGAGCGCAGATCACGGATAAGTATTAAAAAGTGCTGTCGAGGCCGCAGTGGAAGTGACTAATTGGCTGATGCACGGACCTCCAGTGTACAGCTCATGTTTCAGGTGCGTCGGACTGTCAGTGACTCAATTTTCTGGGCCCAACTCCGCGTTCGGTGGATTAGTAACTATAGTGGTTGCATGAGGTACTGAGATTGAGCCGTGAAAAGCATTCAAAGTGCGGTTCCTCAACCTATTATTATTAAGACATAAGTTTGCTAGCGCTTTGTTGCAATCGTGTCGTGGAATGCGATTGATGCTTAGCAGTTTCCGGGAAGTACGGACTCATGCCGTTATGTGCGCCAACAAACAGCGCGTGTTTCATTTCGCGCCGGTCGCCTGGCGCGTGTTATGGGATCGCACTTCACCGTGCTGATATCGCTGAGGCGAGGGTTCCTCGAGATATTGGCTTGGCTCGCCAGGCAGTAGTCGTGGTCAGCCCGACTTGGCACGCTAAAGACGAGCCCACGTGCATTCGGTCGGAATCAGTTAGACGTCGAACGATTCGATCCAGCGTGAGGCCTATCCTTTGCCCATTTAACTCCGTATTCACGGTCTCCTTGATACATAGTGTACTTAGTGTTACCAGCGAACTCCGACGCGGACAGTGTCCTCGGAGTATTACCTCCAAAGAAATTCTCGGGCCGAACAGCGTAGTCTATACCGCCTGGGTG
>seq2 length=1200
ATAGGTGTAGTGTGTCTTCATCTTGATGTAAGTTCGTTCACCCAGATCTGCTAAAACGCATGGCATTTTTTTCGCATACGGTCCACTGGCACTATATGATTCCCAGTACTTCGCAGATTTGGGGGGGTAAGAGTCCGCGGAAGCGTTGTTCTGACGCGTACGCATGTTCGGTATTTTTTACGGGTGAGTTGCATCGGTTGTGTATTGGTCCATGTTAAGACGGTTATCGGGCAGGCTTCTCAATGCGGTGAGTCGGGAAGACACTAGCCAGCGAAATTATGTGATCGCTGGAATAGGATCGATGTAGCAACGACACTTTCCTGGCCTACAGACGGACTTGGACCGGATCAATCGTCTTATATAATAATACACGTCGCAGAACGGTCTGTGTATAGGACCGGTAGAATGAGTAGTTCATACTCCGGCCCGCAGGTACCCCTGTACGCATGAAAGTCCAAGCTCTCGCTGAACCGACACCTCTAGCCGAGGTACGTATGCATGACCTGGTTGTTCTCTTCGGGTCACGACAGTTGCCTATTTACGCTCGGATACCAGGAAACTTTGCCGGGAGTTCGCCCCCAGTAGTTCCCGGGTTGGGGTCGGGGTGTTCTGCCGATTACCGGATGTATCTCACCTGAGATTCAGCATCGGTGCGAACATCGTGAATCCTAAAGGTTGAACAAAGGAAGGCCTCCATGCGTTGGAAAGTCCTCGAAGTGGAGAAGTCTATCGTAGATCAACCGATAGGCAATGAAAAGAAAAAGCGCAACAGACGCCACGCTTCTAGATCGCAGTTGGCCTTTTAATGGCGAATCCATTTACCGAGCGAAGAAAAAGCCTGGCTAGCTTGTTTAAAACTGGTAACACTGAATCTCCGAAAGAGTAGCTATAGGCTCCCAGCACAGCCTGCGGCTGGCGCCAACGCCTAACGAAAATGCCAATCCACTTAGTTGTGTTAACTGTCTCCCCACTATATGCGGCTTACCAGGGAGTGTAATTTCTGGCGATGACCAGCGTTTCCTTTGGGTTCCGTCGAATTCCTTAGATCTAGGACAGCAGTTCGAATTACTTGGCGTGGTCGCATCAGGACTTCGCGTAGTGGCTATCCAGATCATAGACTGAGTCACGTATTTGACGCCAGACCTAAGACCCCACGATGGTTTCTAGTCGTAACTTGAGTGAGCTAGCTCGCCTCGTGTC
ORF prediction
fasta_tools random_nucl -n seq1,seq2 -l 1000,1200 | fasta_tools ORF_finder -c -
>seq1 length=42 ORF_prediction
MRLMLSSFREVRTHAVMCANKQRVFHFAPVAWRVLWDRTSPC*
>seq2 length=87 ORF_prediction
MIWIATTRSPDATTPSNSNCCPRSKEFDGTQRKRWSSPEITLPGKPHIVGRQLTQLSGLAFSLGVGASRRLCWEPIATLSEIQCYQF*
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