🦠 A comprehensive R package for deep mining microbiome
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Updated
Jul 24, 2024 - R
🦠 A comprehensive R package for deep mining microbiome
Network construction, analysis, and comparison for microbial compositional data
A list of R environment based tools for microbiome data exploration, statistical analysis and visualization
This repo contains the R microshades package, which contains a color blind accessible color palette with 30 unique colors and functions for applying these colors to microbiome data.
Track, Analyze, Visualize: Unravel Your Microbiome's Temporal Pattern with MicrobiomeStat
Analyses in R and Python Using curatedMetagenomicData
GDmicro - Use GCN and Deep adaptation network to classify host disease status based on human gut microbiome data.
A Bayesian model for the differential abundance analysis of microbiome sequencing data
The scripts contained in this repository relate directly to the work conducted by the Tree Root Microbiome Project (TRMP) led by Dr Steve Wakelin.
Exploring different database implementations for clinical microbiome data
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.
Microbiome Diversity Inspector - A platform for visual analysis of microbiome data.
A microbiome knowledge graph was constructed using data from the Human Microbiome Project, IBD cohort. This project was done as a part of my dissertation for my MSc in Health Data Science with The University of Manchester. It was done as an internship with Zifo RnD Solutions, a leading Scientific Informatics Company.
A Shiny interface for the MicrobiomeStat R package, designed to facilitate analysis and visualization of microbiome data.
Code to reproduce the analyses from the paper "Benchmarking microbiome transformations favors experimental quantitative approaches to address compositionality and sampling depth biases"
A database for storing and analyzing omics data
Analyzing microbiome data from Gigante, Barro Colorado, Panama. Part of an Undergraduate Thesis (defended on May 13th, 2022).
Python utility to generate distance matrices, perform PCoAs and generate taxonomic summaries using simple tab-separated feature tables.
I performed PCA and t-SNE on the microbiome dataset and visualized the data in 2D space. I also report what I learned from the PCA and t-SNE analyses.
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