Modular command-line solution for visualisation, quality control and taxonomic partitioning of genome datasets
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Updated
Aug 21, 2024 - Python
Modular command-line solution for visualisation, quality control and taxonomic partitioning of genome datasets
Simple statistical identification and removal of contaminants in marker-gene and metagenomics sequencing data
VerifyBamID2: A robust tool for DNA contamination estimation from sequence reads using ancestry-agnostic method.
Recentrifuge: robust comparative analysis and contamination removal for metagenomics
The LM Contamination Index is a manually created database of contamination evidences for LMs.
Detecting contamination in NGS data and multi-species analysis
RawHash is the first mechanism that can accurately and efficiently map raw nanopore signals to large reference genomes (e.g., a human reference genome) in real-time without using powerful computational resources (e.g., GPUs). Described by Firtina et al. (published at https://academic.oup.com/bioinformatics/article/39/Supplement_1/i297/7210440)
Rapid and simple taxonomic profiling of genome and metagenome contigs
GRIMER performs analysis of microbiome studies and generates a portable and interactive dashboard integrating annotation, taxonomy and metadata with focus on contamination detection.
This project is created by the Hao Lab at the Chemistry Department in George Washington University, Washington, D.C. This project aims to provide contaminant protein FASTA and spectral libraries that can be universally applied to DDA and DIA proteomics and freely accessible for the proteomics community.
Remove human reads from a sequencing run
Consensus calling (or "reference assisted assembly"), chiefly of ancient mitochondria
Module and script to remove contamination in assembled genomes before submission to ncbi
Conta is an R package to detect cross contamination and source of contamination
Analytical solutions for groundwater contaminant transport
DecontaMiner is a tool designed and developed to investigate the presence of contaminating sequences in unmapped NGS data. It can suggest the presence of contaminating organisms in sequenced samples, that might derive either from laboratory contamination or from their biological source, and in both cases can be considered as worthy of further in…
Benchmarking different ways of doing read (taxonomic) classification, with a focus on removal of contamination and MTB classification
Automated pipeline for HGT and contaminant detection in an assembled, annotated genome
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