To implement a general framework to quantitatively infer Community Assembly Mechanisms by Phylogenetic-bin-based null model analysis, abbreviated as 'iCAMP' (Ning et al 2020) <doi:10.1038/s41467-020-18560-z>. It can quantitatively assess the relative importance of different community assembly processes, such as selection, dispersal, and drift, for both communities and each phylogenetic group ('bin'). Each bin usually consists of different taxa from a family or an order. The package also provides functions to implement some other published methods, including neutral taxa percentage (Burns et al 2016) <doi:10.1038/ismej.2015.142> based on neutral theory model and quantifying assembly processes based on entire-community null models ('QPEN', Stegen et al 2013) <doi:10.1038/ismej.2013.93>. It also includes some handy functions, particularly for big datasets, such as phylogenetic and taxonomic null model analysis at both community and bin levels, between-taxa niche difference and phylogenetic distance calculation, phylogenetic signal test within phylogenetic groups, midpoint root of big trees, etc. Version 1.3.x mainly improved the function for 'QPEN' and added function 'icamp.cate()' to summarize 'iCAMP' results for different categories of taxa (e.g. core versus rare taxa).

Running Focused Identification of the Germplasm Strategy (FIGS) to make best subsets from Genebank Collection.

Implements the integrative conditional autoregressive horseshoe model 
    discussed in Jendoubi, T., Ebbels, T.M. Integrative analysis of time course metabolic data and biomarker discovery. 
    BMC Bioinformatics 21, 11 (2020) <doi:10.1186/s12859-019-3333-0>.
    The model consists in three levels: Metabolic pathways level modeling interdependencies between
    variables via a conditional auto-regressive (CAR) component, integrative analysis level to identify
    potential associations between heterogeneous omic variables via a Horseshoe prior and experimental
    design level to capture experimental design conditions through a mixed-effects model.
    The package also provides functions to simulate data from the model, construct pathway matrices,
    post process and plot model parameters.