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accelerated_advanced_python_weeks3_4

This repository contains jupyter notebooks for weeks 3 and 4 of Accelerated Computational Biology class. This tutorial will cover advanced NumPy lectures including several algorithms used for data analysis in computational biology

accelerated_intro_to_compbio_part_2

Part 2 of the "Accelerated intro to Computational Biology for Biologists" course for the Master's Programme in Computational Biology, Universidad Politecnica de Madrid. This covers the first 2 weeks (~24 hours) of material, taught by Mark Wilkinson.

accelerated_intro_wilkinsonexams

Exam Questions and instructions for the Accellerated Introduction to Computational Biology M.Sc. course - Wilkinson Section

anthocyanins

Analisys performed for the TDThub output when using the Blastp Tool, using anthocianins regulation as example

basicregistation

This is a basic registration method in django

biofx_python

Code for Mastering Python for Bioinformatics (O'Reilly, 2021, ISBN 9781098100889)

chipseq

ChIP-seq peak-calling, QC and differential analysis pipeline.

dap-seq-pipeline

TF-DNA-binding assay analysis pipeline

differentialabundance

Differential abundance analysis for feature/ observation matrices from platforms such as RNA-seq

dnashapevalues

Pipeline to get the values of Roll, MGW, ProT and HelT from a genome.fa file

gem3-mapper

GEM-Mapper v3

gff3_parser

A package for parsing gff3 (general feature format) files into pandas dataframes

macs-analysis-pipelines

Pipeline codes for analyzing various genomics datasets based on MACS3

mepigram

Methylated DNA motif discovery tool

methylationbisulfite

This is a pipeline developed to analyce bisulfite and Dapseq experiments

my_cookbook_model

new.py

Python program to write new Python programs

nf-core-wgcnamodules

pandas-docker

Project to build a docker container with python and pandas.

public-apis

A collective list of free APIs

pyrpipe

Reproducible bioinformatics pipelines in python. Import any Unix tool/command in python.

pytest

The pytest framework makes it easy to write small tests, yet scales to support complex functional testing

pywgcna

PyWGCNA is a Python package designed to do Weighted correlation network analysis (WGCNA)

rnaseq

RNA sequencing analysis pipeline using STAR, RSEM, HISAT2 or Salmon with gene/isoform counts and extensive quality control.

roldanjg

My personal repository.

savings_calculator

tmuxp

:computer: tmux session manager. built on libtmux

trimgalore

A wrapper around Cutadapt and FastQC to consistently apply adapter and quality trimming to FastQ files, with extra functionality for RRBS data

wgcnamodules_testdata

Toy data generated to facilitate the use and testing of the pipeline wgcnamodules created for the book chapter-