A general metagenomics data mining system focus on robust microbiome research

Code for design of diagnostic PCR primers, and metabarcoding markers.

fast BAM/CRAM depth calculation for WGS, exome, or targeted sequencing

GUI/CommandLine Tool Box for biologistists to utilize NGS data.

Community-provided extensions to Seurat

Graph Neural Network Library for PyTorch

A comprehensive tutorial about GWAS and PRS

MMseqs2: ultra fast and sensitive search and clustering suite

Community-curated list of software packages and data resources for single-cell, including RNA-seq, ATAC-seq, etc.

This is an an algorithm, Hi-C Matrix Balancing (HCMB), based on iterative solution of equations, combining with linear search and projection strategy to normalize the hi-C original interaction data.

FRMC is a fast and robust imputation software for single cell RNA-Seq data.

主要存储Datawhale组队学习中“数据挖掘/机器学习”方向的资料。

Implementation of Vision Transformer, a simple way to achieve SOTA in vision classification with only a single transformer encoder, in Pytorch

Code for the book Deep Learning with PyTorch by Eli Stevens, Luca Antiga, and Thomas Viehmann.

A Python toolbox for performing gradient-free optimization

software tools for haplotype assembly from sequence data

Uniform Manifold Approximation and Projection

《Designing Data-Intensive Application》DDIA中文翻译

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 form…

Python framework for fast (approximated) nearest neighbour search in large, high-dimensional data sets using different locality-sensitive hashes.

Runs a combination of tools to generate structural variant calls on whole-genome sequencing data

Tangible and Practical Deep Learning Projects Repository for Healthcare such as Cancer, Drug Discovery, Genomic and More

Multi-Omics Factor Analysis

Python 2.7 implementation of network-based stratification (NBS) algorithm from Hofree et al (Nature Methods 2013)