Quickly search, compare, and analyze genomic and metagenomic data sets.
-
Updated
Jun 26, 2024 - Python
Quickly search, compare, and analyze genomic and metagenomic data sets.
Fast taxonomic classification of metagenomic sequencing reads using a protein reference database
Accurate metagenomic profiling && Fast large-scale sequence/genome searching
Amplicon sequencing analysis workflow using DADA2 and QIIME2
ultrafast genome querying and taxonomic profiling for metagenomic samples by abundance-corrected minhash.
Highly parallelised multi-taxonomic profiling of shotgun short- and long-read metagenomic data
Metabuli: specific and sensitive metagenomic classification via joint analysis of DNA and amino acid.
Massively parallel phylogenetic placement of genetic sequences
FlexTaxD (Flexible Taxonomy Databases) - Create, add, merge different taxonomy sources (QIIME, GTDB, NCBI and more) and create metagenomic databases (kraken2, ganon and more )
Create BIOM-format tables (http://biom-format.org) from Kraken output (http://ccb.jhu.edu/software/kraken/, https://github.com/DerrickWood/kraken).
Tag and recommend Python exercises based on algorithmic features
PyTorch implementation of Metric-Guided Prototype Learning for hierarchical classification.
This repository contains all the source files required to run DeLUCS, a deep learning clustering algorithm for DNA sequences.
Fast and space-efficient taxonomic classification of long reads
Lemur is a tool for rapid and accurate taxonomic profiling on long-read metagenomic datasets
Phylogenetic Placement Evaluation Workflows : Benchmark placement software and different reference trees
Collection of notebooks describing the basic analysis workflow for a 16S rRNA gene amplicon sequencing project
📓 Companion code for Grenié et al. 2022 MEE "Harmonizing taxon names in biodiversity data: a review of tools, databases, and best practices" preprint: 10.32942/osf.io/e3qnz
CyanoSeq: A curated cyanobacterial 16S rRNA database for next-generation sequencing
A pipeline to identify (and remove) certain sequences from raw genomic data. Default taxa to identify (and remove) are Homo and Homo sapiens. Removal is optional.
Add a description, image, and links to the taxonomic-classification topic page so that developers can more easily learn about it.
To associate your repository with the taxonomic-classification topic, visit your repo's landing page and select "manage topics."