Consensus calling (or "reference assisted assembly"), chiefly of ancient mitochondria

Analytical solution for Contaminant Transport in Groundwater

Repositorio para análisis y publicación de datos de contaminación en Andalucía

Module and script to remove contamination in assembled genomes before submission to ncbi

Python based machine-learning scripts that generate real-time predictions of the water quality on the shores of the larger Montreal island for the water activities aficionados The predictions are displayed online interactively on an OpenShift server built with the LAMP stack.

Nextflow pipeline for Conpair (concordance and contamination estimator)

Contamination detection workflow based on mtDNA

Module simulating groundwater flow and contaminant transport in multiple groundwater zones (saturated and unsaturated)

Parameter estimation of seeding and contamination rates on a triangular lattice using the method of simulated moments (MSM).

Conta is an R package to detect cross contamination and source of contamination

Conta is an R package to detect cross contamination and source of contamination

autoConTAMPR: Automatic Contingency Table Analysis of Minority Peak Ranks

Reference-based, heuristic algorithm for identification of potential contaminants in mothur-formatted OTU tables

MitoSIS (Mitochondrial Species Identification System) is a wrapper for mitochondrial genome assembly and identification of sample contamination or mislabeling.

Water quality monitoring in river for pollution control applicating continuous conductivity monitoring. This is for evaluation of pollution level and its fluctuation as BOD5 converting by Conductivity value utilizing Arduino Nano.

R codes developed for East Chicago PCB soil paper. Codes describe how to create the maps and figures (ECSoilFigures.R), as well as all the statistical analyses (ECSoilStatTest.R) performed in the paper. All data are available and download from Pangaea. This is part of Project 6 of the ISRP (https://iowasuperfund.uiowa.edu/)

Automated pipeline for HGT and contaminant detection in an assembled, annotated genome

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..(Publication pending) 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.

Simple statistical identification and removal of contaminants in marker-gene and metagenomics sequencing data