biofile-kit 0.0.1

Bioinformatics File Operations Toolkit.

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*