arupgsh Goto Github PK

2016-summer-workshop

ISCB DC Area Regional Student Group - Summer 2016 Workshop

2017-04-03-adv-r-progr-embl

Advanced R programming course at EMBL, 3-4 April 2017

advanced-shiny

Shiny tips & tricks for improving your apps and solving common problems

affordabee

amazon-genomics-cli

arupdev

Personal website usign Jekyll theme, migration from hugo.

arupgsh

b4_genomics_workshop_2018

The Workshop on Genomic Applications in Healthcare & Translational Research took place on December 10-23, 2017

bam-tricks

Tip and tricks for BAM files

bi-be-cs-183-2023

Introduction to Computational Biology and Bioinformatics Course at Caltech, 2023

biolord

biopython

Official git repository for Biopython (originally converted from CVS)

bustools-notebooks

clinicalgradednaseq

Automated next generation DNA sequencing analysis pipeline suited for clinical tests, with >99.9% sensitivity to Sanger sequencing at read-depth>18

codechef_solutions

Codechef

deep-learning-nano-foundation

Udacity's Deep Learning Nano Foundation program.

e-mtab-6141

Data from Lewis, Barnes, Blighe et al., Cell Rep. 2019 Aug 27; 28(9): 2455–2470.e5.

freecodecamp

funkyheatmap

Visualising data frames as funky heatmaps 📊

gentb_downloader

Download analysis results from https://gentb.hms.harvard.edu/

gwas_gemma

Perform GWAS with gemma in a simple pipeline

hdwgcna

High dimensional weighted gene co-expression network analysis

heredity.github.io

Temporary website for heredity.bio

hts-specs

Specifications of SAM/BAM and related high-throughput sequencing file formats

intel-models

Model Zoo for Intel® Architecture: contains Intel optimizations for running deep learning workloads on Intel® Xeon® Scalable processors

kraken2-env

leprae_lineage_caller_test

lowcostopenaccess

This is a resource where people can get information on journals where they can publish at waived or subsidised APC.

microbial_amr_ml

Code repository for machine learning and computational analysis of large-scale microbial genomics data (https://rdcu.be/9rHj)

mlalgorithms

Minimal and clean examples of machine learning algorithms