github.com - Tinycov is a small standalone command line utility written in python to plot the coverage of a BAM file quickly. This software was inspired by Matt Edwards' genome coverage plotter.
To install the stable version: pip3 install --user...
pypi.python.org - Orange Bioinformatics extends Orange, a data mining software package, with common functionality for bioinformatics. The provided functionality can be accessed as a Python library or through a visual programming interface (Orange Canvas). The latter...
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
More...
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...
dash.plot.ly - Dash is a web application framework that provides pure Python abstraction around HTML, CSS, and JavaScript.
Dash Bio is a suite of bioinformatics components that make it simpler to analyze and visualize bioinformatics data and interact with them in...
https://www.uksh.de/jobs/Stellenangebote-nr-20190570-p-8.html
Your profile:
Degree in bioinformatics, biostatistics, or equivalent
Experience in the processing and analysis of large-scale genomics data using compute clusters / high-performance...
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....