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ml-genomics-resources

Machine Learning for Genomics and Therapeutics Resources (Cell Patterns)

mmap

Computational tool the prioritizing the genetic candidates based on the protein functional features

motiftools

TF Motif Variant Analysis

mrsimplify

TwosampleMR and MultivariableMR perform with simple commands without prior knowledge or having to go through lengthy boring protocols

mummer

Mummer alignment tool

mutated_codons

Python code to locate the codon for single base change

nanotei

A pipeline for detection of non-reference transposon insertions using Nanopore data

nasqar

NASQAR: A web-based platform for High-throughput sequencing data analysis and visualization

orange-bio

orf_mm10

small ORF file for mm10 (mouse) genome for UTRannotator vep Plugin

palmer

Pre-mAsking Long reads for Mobile Element inseRtion

pdbtools

A set of tools for manipulating and doing calculations on wwPDB macromolecule structure files

peer

A factor analysis package

pepper

PEPPER-Margin-DeepVariant

plotsr

Tool to plot synteny and structural rearrangements between genomes

pnet_prostate_paper

P-NET, Biologically informed deep neural network for prostate cancer classification and discovery

prospr

ProSPr: Protein Structure Prediction

proteogenomics

Analysis to map update CHO genome annotation using protegenomics method

pynoramic

pyntheon

Pyntheon; A post translational modifications (PTMs) mapping tool for 87 different species, these PTMs are taken from a large array of popular lab specimens.

pyntheon-r

r version of Pyntheon; A post translational modifications (PTMs) mapping tool for 87 different species, these PTMs are taken from a large array of popular lab specimens

pyrthenon

A Machine Learning Tool to Predict Novel Therapeutics of Infectious diseases

pythagoras

pythohar

radar

RADAR source code

read_length_sv_discovery

rna-seq-analysis

RNAseq analysis notes from Ming Tang

rnaseq_tutorial

Informatics for RNA-seq: A web resource for analysis on the cloud. Educational tutorials and working pipelines for RNA-seq analysis including an introduction to: cloud computing, critical file formats, reference genomes, gene annotation, expression, differential expression, alternative splicing, data visualization, and interpretation.

rosettafold

This package contains deep learning models and related scripts for RoseTTAFold

rsem

RSEM: accurate quantification of gene and isoform expression from RNA-Seq data