-
Notifications
You must be signed in to change notification settings - Fork 52
Home
- (Probabilistic?) mixed effects model examples in the DAA section?
- Catboost
- BugSigDB and related R packages bugsigdbr and BugSigDBStats
- SCpubr-book
- OSCA
- MSMB
- BiocViews on microbiome
- rOpenSci development guide
Sample size calculator for microbiome data would be helpful for many.
-
mPower by Lu Yang is now in the making
-
Multiple testing post-hoc correction for PERMANOVA, examples (CR):
mctoolsr::calc_pairwise_permanovas
GUniFrac: Generalized UniFrac Distances, Distance-Based Multivariate Methods and Feature-Based Univariate Methods for Microbiome Data Analysis CRAN package with A suite of methods for powerful and robust microbiome data analysis including data normalization, data simulation, community-level association testing and differential abundance analysis. It implements generalized UniFrac distances, Geometric Mean of Pairwise Ratios (GMPR) normalization, semiparametric data simulator, distance-based statistical methods, and feature-based statistical methods. The distance-based statistical methods include three extensions of PERMANOVA: (1) PERMANOVA using the Freedman-Lane permutation scheme, (2) PERMANOVA omnibus test using multiple matrices, and (3) analytical approach to approximating PERMANOVA p-value. Feature-based statistical methods include linear model-based methods for differential abundance analysis of zero-inflated high-dimensional compositional data.
POSTm: Phylogeny-Guided OTU-Specific Association Test for Microbiome Data - Implements the Phylogeny-Guided Microbiome OTU-Specific Association Test method, which boosts the testing power by adaptively borrowing information from phylogenetically close OTUs (operational taxonomic units) of the target OTU. This method is built on a kernel machine regression framework and allows for flexible modeling of complex microbiome effects, adjustments for covariates, and can accommodate both continuous and binary outcomes.
GMEmbeddings: An R Package to Apply Embedding Techniques to Microbiome Data
- alto nested topic models
- fido (stray) for Bayesian analysis of balances
- Probabilistic topic models / LDA and differential topic analysis from Holmes & Jeganathan
- Probabilistic PCA implementation and examples for
miaverse - Multiple testing correction vs. hierarchical probabilistic testing
- Power calculations
- LinDA
- songbird
- More examples on ratio-based tests
- ANCOM-II not mentioned in OMA examples (ANCOM-BC is but it is not in this review; which one is better..?)
- Check the book Statistical Analysis of Microbiome Data with R by Yinglin XiaJun SunDing-Geng Chen (2018); cite and confirm that key methods are covered by OMA, or omission justified
- OGU support
- phylofactor; support for phylogenetic factorization based on phILR
- Using tidytree? Could be processed and visualized via tidytree, treeio, ggtree and ggtreeExtra
Add a link to iheatmapr; consider if an example would be useful (or not) in addition to pheatmap examples.
Generic points on heatmaps:
-
meltAssay is readily useful to prepare data for ggplot-based heatmaps; is there a need for other tse data converters for pheatmap or some other heatmap packages?
-
Check if there are good existing resources for heatmaps on the single cell experiment side (OSCA book?) or other
-
Consider heatmap example with philr balances, in addition to typical abundance-based heatmaps. First finalize the philr PR, however.
- Add neat & neatsort in miaViz and then also add heatmap examples to OMA using these?
- qiitr; add support for data retrieval and analysis from QIITA
Sankaran & Holmes (2019) Multitable Methods for Microbiome Data Integration
POMS for Integrating phylogenetic and functional data in microbiome studies. Available as an R package
- https://www.emilyzabor.com/tutorials/survival_analysis_in_r_tutorial.html#Part_1:_Introduction_to_Survival_Analysis
- alpha diversity
- distance from a group
- community composition
- Relevant R packages: rms; survival.. etc.
-
iSEE
-
iSEEde for DA analysis
-
Interactive tables
-
3D visualizations
-
Interactive heatmap example with heatmaply after we have this on a server?
-
tidySummarizedExperiment potential for OMA examples
-
SingleCellExperiment & seurat tools
BiomeHorizon: Visualizing Microbiome Time Series Data in R biomehorizon pkg biomehorizon user guide
Turnover indices
- Walkthrough to TreeSE from microbiome perspective? First review resources in other sources, including SE, TreeSE, SCE, OSCA, scater, seurat etc.
- Rank abundance curve
- Forest plot
- UpSet plots
- Power calculations
- RDA & other supervised ordination techniques
- Table examples
- Density plot
- Volcano plot
- Horseshoe effects
- Visualization artefacts (enterotype w/o colors; forced clustering; biased groups etc.) for educational purposes
- Cross-sectional
- Case-control
- Intervention
- Individual
- Longitudinal time series analysis & simulation (seqtime/microsimR integration)?
- Spatial
- Networks
- Tipping elements & bimodality
- Forensics / source tracking ref1; ref2
- file2meco
- maaslin2 (Mallick H et al., 2020)
- specificity
Write the manuscript collaboratively using Manubot
-
Add comparison between TreeSE vs. phyloseq systematically; what are the main differences, what are key similarities, what are the pros & cons of each, how to convert? MAE to bind.
-
Speed comparisons?
Explain Difference between PLS-DA, (dbRDA), ... good short explanation and considering adding support for PLS-DA (from mixOmics for instance)
- Examples on tree based alpha, beta, diffab (hierarchical tests?)
- microbiome workflow
- analysis types
Go through for useful functionality (supporting SE/SCE):
- [scater]
- [scuttle]
- scran
- btools
- Tools-Microbiome-Analysis/
- Coverage and especially Good's coverage; these are simple to implement from scratch