Learn R Programming

⚠️There's a newer version (1.5.12) of this package.Take me there.

iCAMP (version 1.3.4)

Infer Community Assembly Mechanisms by Phylogenetic-Bin-Based Null Model Analysis

Description

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) . 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) based on neutral theory model (Sloan et al 2006) and quantifying assembly processes based on entire-community null models ('QPEN', Stegen et al 2013) . 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).

Copy Link

Version

Install

install.packages('iCAMP')

Monthly Downloads

1,763

Version

1.3.4

License

GPL-2

Issues

Pull Requests

Stars

Forks

Maintainer

Daliang Ning

Last Published

January 9th, 2021

Functions in iCAMP (1.3.4)

RC.pc

Modified Raup-Crick index based on Bray-Curtis similarity
bNTI.big

Beta nearest taxon index (betaNTI) from big data
bNTI.bin.big

Calculate beta nearest taxon index (betaNTI) for each phylogenetic bin
RC.bin.bigc

Calculate modified Roup-Crick index based on Bray-Curtis similarity for each phylogenetic bin
bNRI.bin.big

Calculate beta net relatedness index (betaNRI) for each phylogenetic bin
bNRIn.p

Calculate beta net relatedness index with parallel computing
dniche

Calculate niche difference between species
dist.3col

Transform distance matrix to 3-column matrix
bmntd

beta mean nearest taxon distance (betaMNTD)
bNTIn.p

Calculate beta nearest taxon index (betaNTI) with parallel computing
bmpd

Beta mean pairwise distance (betaMPD)
bmntd.big

beta mean nearest taxon distance (betaMNTD) from big data
iCAMP-package

Infer Community Assembly Mechanisms by Phylogenetic-bin-based null model analysis
NTI.p

Calculate nearest taxon index (NTI) with parallel computing
dist.bin.3col

Convert a list of dist (or matrixes) to a matrix
icamp.big

Infer community assembly mechanism by phylogenetic-bin-based null model analysis
icamp.cate

Summarize iCAMP result for different categories of taxa
icamp.out

Example output of function icamp.big
NRI.p

Calculate net relatedness index (NRI) by parallel computing.
match.2col

Check the consistency of the first two columns of different matrixes
example.data

A simple example dataset for test
match.name

Check and ensure the consistency of IDs in different objects.
maxbigm

Find maximum value in a big matrix
mntdn

Mean nearest taxon distance (MNTD)
mpdn

Mean pairwise distance (MPD)
ps.bin

Test within-bin phylogenetic signal
qp.bin.js

Calculate relative importance of community assembly processes
cohend

Cohen's d effect size
change.sigindex

Change significance index option in iCAMP analysis
midpoint.root.big

Midpoint root a large phylogeny
qpen

Quantifying assembly processes based on entire-community null model analysis
snm

Estimation of neutral taxa percentae and dispersal rate
tree.droot

Distance from root to tip(s) and node(s) on phylogenetic tree
taxa.binphy.big

Phylogenetic binning based on phylogenetic tree
icamp.boot

Bootstrapping analysis of icamp results
icamp.bins

Summarize iCAMP result in each bin
tree.path

List nodes and edge lengthes from root to each tip and/or node
pdist.big

Pairwise phylogenetic distance matrix from big tree
null.norm

Normality test for null values