personal metagenomic analysis tools
- Best practices for analysing microbiomes
- Current challenges and best-practice protocols for microbiome analysis
- Shotgun metagenomics, from sampling to analysis.
- A practical guide to amplicon and metagenomic analysis of microbiome data
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paper: Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing, "For datasets where a mock community is not included for calibration, we recommend the conservative threshold of (c = 0.005%). c is the OTU abundance threshold".
See also in qiime forum: feature filter: The abundance filtering recommendation was specific to the OTU picking pipelines in QIIME1 (but would probably still apply if you use the OTU picking pipelines in QIIME2), and is not tested in conjunction with dada2 or deblur, and are most likely unnecessary (based on the results reported in the original papers for dada2 and deblur) or even conflicting.
- A broken promise: microbiome differential abundance methods do not control the false discovery rate
- Analysis of microbial compositions: a review of normalization and differential abundance analysis
- Normalization and microbial differential abundance strategies depend upon data characteristics
- Waste Not, Want Not: Why Rarefying Microbiome Data Is Inadmissible
- LEfSe, Metagenomic biomarker discovery and explanation
- DESeq2, Moderated estimation of fold change and dispersion for RNA-seq data with DESeq2
- edgeR, edgeR: a Bioconductor package for differential expression analysis of digital gene expression data
- metagenomeSeq, Differential abundance analysis for microbial marker-gene surveys
- ANCOM, Analysis of composition of microbiomes: a novel method for studying microbial composition
- ANCOMBC, Analysis of compositions of microbiomes with bias correction
- animalcules, Note this R package is not only for differential analysis, it is a comprehensive analysis toolkit for microbiome analysis workflow. Specifically, it supports biomarker identification by training a logistic regression or random forest model with cross-validated biomarker performance evaluation.
- review paper: Reconstructing organisms in silico: genome-scale models and their emerging applications, review on overrall development of genome-scale models and their applications, and the emerging areas in genome-scale modeling of microbioal phenotypes.
- review paper: Current status and applications of genome-scale metabolic models
- paper: CoBAMP: a Python framework for metabolic pathway analysis in constraint-based models. software: CoBAMP.
- paper: Fast automated reconstruction of genome-scale metabolic models for microbial species and communities. software: carveme, a python-based tool for genome-scale metabolic model reconstruction.
- paper: reconstruction of genome scale metabolic models directly from metagenomes. software: metaGEM, a Snakemake pipeline for the generation of MAGs, reconstruction of GEMs, and simulation of cross-feeding interactions within microbial communities.
- moped - A Python package for metabolic modelling and topological analysis.
- MICOM: Metagenome-Scale Modeling To Infer Metabolic Interactions in the Gut Microbiota.
- paper: Using Genome-scale Models to Predict Biological Capabilities
- paper: Understanding the host-microbe interactions using metabolic modeling
- review paper: Microbial interactions: from networks to models
- paper: Metabolic dependencies drive species co-occurrence in diverse microbial communities. software: smetana, a tool to analyse interactions in microbial communities.
- paper: MMinte, an application for predicting metabolic interactions among the microbial species in a community.
- paper, algorithm: Ecology-guided prediction of cross-feeding interactions in the human gut microbiome, GutCP: a new ecology-guided method to infer and predict cross-feeding interactions in the human gut microbiome. It can also be used to pridict the metabolomic composition based on a original cross-feeding network (in which nodes are metabolites or microbes).
- manta: a Clustering Algorithm for Weighted Ecological Networks, used for networks with negative edges (microbial community ecological networks).
- Learning representations of microbe–metabolite interactions, inferring microbio-metabolite interactions using neural networks (https://github.com/biocore/mmvec) to estimate the conditional probability that each molecule is present given the presence of a specific microorganism.
- HumanMetagenomeDB, explore and download curated human metagenomes metadata, paper in 2021 NAR database.
- MASI, interaction between human microbiota and active substances, especially for those therapeutically-relevant substances such as clinical used drugs and traditional medicines/herbs, paper in 2021 NAR database
- GIMICA, host genetic and immune factors shaping human microbiota, paper in 2021 NAR database
- gutMDisorder, a manually curated database, aims at providing a comprehensive resource of dysbiosis of the gut microbiota in disorders and interventions. paper in 2020 NAR database
- GMrepo, a database of curated and consistently annotated human gut metagenomes. paper in 2020 NAR database
- HMPDACC, Human Microbiome Project Multi-omic data resource, paper in 2021 NAR database
- Peryton, database of experimentally supported microbe-disease associations. paer in 2021 NAR database.
- TerrestrialMetagenomeDB, a public repository of curated and standardized metadata for terrestrial metagenomes, paper in 2020 NAR dabase.
- MicrobiomeDB, a systems biology platform for integrating, mining and analyzing microbiome experiments, can be used to identify experimental variables associated with changes in microbial community structure. paper in 2018 NAR database.
- MGnify, formely EBI metagenomics, provides a free to use platform for the assembly, anal- ysis and archiving of microbiome data derived from sequencing microbial populations that are present in particular environments. papar in 2020 NAR database](https://doi.org/10.1093/nar/gkz1035)