Training materials for METAGENOTE
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Updated
Mar 30, 2020
Training materials for METAGENOTE
Longitudinal OSA Experiments - Lesion, Microbiome, Metabolome
Bash scripts for running QIIME 1.9 and a Snakemake workflow to automate it using singularity container images.
Workflow and R scripts for Giongo et al. (2024)
A python implementation of the decontam R package for ASV filtering.
Analysis of Multiple Circadian/Longitudinal Datasets
Predictive model, utilizes several machine learning algorithms to predict patient disease status from abundance data
Supporting materials for the manuscript "Characterisation and comparison of semen microbiota and sperm function in men with infertility, recurrent miscarriage, or proven fertility
In this repository live the bash, R and Julia scripts used to explore the microdiversity of the prokaryotic community at Uranouchi Inlet (9-sample time-series) by means of metagenomic shotgun sequencing under the supervision of the Ogata Lab.
This repo details the multi-stressor exposure experiment conducted in August 2022 at Hawaii Institute of Marine Biology (HIMB) in Kaneohe Bay. In this experiment coral fragments were exposed to increasing levels of phthalate pollution and thermal stress for 48 hours.
microbiome analysis of ant colonies
Vaginal microbiome data analysis using QIIME2 in women with gynecologic cancer.
General purpose package containing useful functions for microbiome analysis pipelines
Code for the paper "Spatial variability of the microbiome in chronic rhinosinusitis is associated with the patients’ clinical characteristics but not with sinus ostia occlusion" by Szaleniec et al. 2022
R/C code for Bayesian variable selection for Dirichlet-multinomial regression models. Accompany paper: Wadsworth et al. (2016). An Integrative Bayesian Dirichlet-Multinomial Regression Model for the Analysis of Taxonomic Abundances in Microbiome data. BMC Bioinformatics 18:94.
Generic code for performing microbiome-wide association studies with a variety of models
Statistical and Computational methods for Microbiome Studies.
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