A flexible metagenomic pipeline combining read-based, assemblies and MAGs with downstream analysis

Track, Analyze, Visualize: Unravel Your Microbiome's Temporal Pattern with MicrobiomeStat

MerCat2: python code for versatile k-mer counting and diversity estimation for database independent property analysis for metaome data

MGX graphical user interface

Graph-based assembly phasing

The purpose of this repository is the metagenomic analysis of FastQ files

MicrobiomeStat Tutorial Repository: This is a comprehensive resource for learning how to use the MicrobiomeStat package. It provides a step-by-step guide to effectively analyze complex microbiome data.

Contains all the code and data related to the CS6024 - Algorithmic Approaches to Computational Biology in the topic: Disease detection using metagenomic dataset

Fast sequence vectorization for metagenomics analysis. Converts input sequences into oligonucleotide frequency vectors, fast!

Fast sequence vectorization for metagenomics analysis. Converts input sequences into k-mer coverage vectors, fast! Read more detail in our paperhttps://doi.org/10.1093/bioinformatics/btaa441

VirBot: a protein-based RNA virus detector for metagenomic data

WGS- Metasociomic- analysing bacterial social interactions in metagenomes of longitudinally collected samples of human microbiomes

Repository for workshop study projects in Bioinformatics Institute 2023-2024

Genestrip - Efficient read classification, filtering and k-mer counting for selected groups of species

iMAP v1.0 (Pre-release): Integrated Microbiome Analysis Pipeline

MetaFast is a novel metagenomic analysis tool employing efficient containment search techniques and heuristics for read mapping to achieve significant speedup while maintaining high accuracy. This positions MetaFast as an efficient solution, optimally balancing speed and precision in metagenomic analysis.

StaG Metagenomic Workflow Collaboration

Repository for report for study project «Human Microbiome Research» by Blastim

Lemur is a tool for rapid and accurate taxonomic profiling on long-read metagenomic datasets

Accurate taxonomic classification and abundance profiling using locality-sensitive hashing.