scikit-learn.org - Machine Learning in Python
Simple and efficient tools for data mining and data analysis Accessible to everybody, and reusable in various contexts Built on NumPy, SciPy, and matplotlib Open source, commercially usable - BSD license
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Python is a general-purpose language, which means it can be used to build just about anything, which will be made easy with the right tools/libraries.
Professionally, Python is great for backend web development, data analysis, artificial...
pypi.org - The Environment for Tree Exploration (ETE) is a Python programming toolkit that assists in the recontruction, manipulation, analysis and visualization of phylogenetic trees (although clustering trees or any other tree-like data structure are also...
github.com - Collection of Python libraries to parse bioinformatics files, or perform computation related to assembly, annotation, and comparative genomics.
https://github.com/tanghaibao/jcvi
More at https://github.com/tanghaibao/jcvi/wiki
Subprocess is one of simplest way of running linux command from within python code
Example:
if you want to run fastqc for QC of fastq file:
from subprocess import Popen,PIPE,call
p=Popen(["fastqc","-f","fastq","-o",...
github.com - snakePipes are flexible and powerful workflows built using snakemake that simplify the analysis of NGS data.
DNA-mapping*
ChIP-seq*
RNA-seq*
ATAC-seq*
scRNA-seq
Hi-C
Whole Genome Bisulfite Seq/WGBS
(*Also available in...
github.com - There is a directory for each chapter of the book. Each directory contains a test.py program you can use with pytest to check that you have written the program correctly. I have included a short README to describe each exercise....
Linux, free operating system for computers, provides several powerful admin tools and utilities which will help you to manage your systems effectively and handle huge amount of genomic/biological data with an ease. The field of bioinformatics relies...