sunsetyerin

Web-Dev-For-Beginners

24 Lessons, 12 Weeks, Get Started as a Web Developer

deeplearning-models

A collection of various deep learning architectures, models, and tips

tensor2tensor

Library of deep learning models and datasets designed to make deep learning more accessible and accelerate ML research.

deepmind-research

This repository contains implementations and illustrative code to accompany DeepMind publications

UNCALLED

Raw nanopore signal mapper that enables real-time targeted sequencing

stat453-deep-learning-ss21

STAT 453: Intro to Deep Learning @ UW-Madison (Spring 2021)

awesome-nanopore

A curated list of awesome nanopore analysis tools.

public

Public documents for the Master of Data Science program at the University of British Columbia

IsoQuant

Transcript discovery and quantification with long RNA reads (Nanopores and PacBio)

flotilla

Reproducible machine learning analysis of gene expression and alternative splicing data

nextflow-tutorial

Nextflow training material for introductory tutorial

wf-transcriptomes

wub

Tools and software library developed by the ONT Applications group

pipeline-nanopore-denovo-isoforms

Pipeline for de novo clustering of long transcriptomic reads

enrichment_analysis

A Snakemake workflow for performing genomic region set and gene set enrichment analyses using LOLA, GREAT, GSEApy, pycisTarget and RcisTarget.

conda-move

Move environments from an existing conda installation to another directory

unsupervised_analysis

A general purpose Snakemake workflow to perform unsupervised analyses (dimensionality reduction & cluster analysis) and visualizations of high-dimensional data.

nanoDoc

RNA modification detection using Nanopore raw reads with Deep One Class classification

nonnegative-matrix-factorization

A python program that applies a choice of nonnegative matrix factorization (NMF) algorithms to a dataset for clustering.

Nano3P_Seq

Nanopore 3' end-capture sequencing (Begik et al., bioRxiv 2021)

wf-isoforms

pipeline-polya-diff

Pipeline for testing shifts in poly(A) tail lengths estimated by nanopolish

cornet

Pipelines for correlation network analysis for gene expression data

NMF_unsupervised_clustering

Non-Negative Matrix Factorization for Gene Expression Clustering

nanocompore_pipeline

Nextflow pipeline for nanocompore analysis

General_Clustering_Pipeline

Clusters columns of any data frame

Samples_Clustering_Pipeline

Clusters the sample-based columns of a spreadsheet whose rows correspond to genes

Clustering-Algorithms

Implemented three clustering algorithms: K-means, hierarchical agglomerative clustering with single link (Min), and density-based clustering to find clusters of genes that exhibit similar expression profiles. Compared the performance of each of the algorithms using external Rand index and visualized the clustering results using PCA.

Clustering-Algorithms

1. Implemented clustering algorithms such as K-means, Hierarchical Agglomerative clustering with Single Link (Min), and Density-based clustering to find clusters of genes that exhibit similar expression profiles. 2. The results of these algorithms were validated using Jaccard co-efficient (over 40 %) and Rand Index (over 80 %) as a similarity measure. 3. In addition, implemented MapReduce K-means by setting up a single-node hadoop cluster and verifying its results using traditional K-means implementation.

snakemake-feature-phenotype-correlations

A Snakemake pipeline for computing correlations within and between paired feature and phenotype datasets