bNRIn.p: Calculate beta net relatedness index with parallel computing

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

Calculate beta net relatedness index with parallel computing

Description

Perform null model test based on a phylogenetic beta diversity index, beta mean pairwise distance (betaMPD); calculate beta net relatedness index (betaNRI), or modified Raup-Crick metric, or confidence level based on the comparison between observed and null betaMPD. Run by parallel computing.

Usage

bNRIn.p(comm, dis, nworker = 4, memo.size.GB = 50,
        weighted = c(TRUE, FALSE), rand = 1000, output.bMPD = c(FALSE, TRUE), 
        sig.index = c("SES", "Confidence", "RC", "bNRI"),
        unit.sum = NULL, correct.special = FALSE, detail.null = FALSE,
        special.method = c("MPD", "MNTD", "both"),
        ses.cut = 1.96, rc.cut = 0.95, conf.cut = 0.975,
        dirichlet = FALSE)

Arguments

comm	matrix or data.frame, community data, each row is a sample or site, each colname is a species or OTU or gene, thus rownames should be sample IDs, colnames should be taxa IDs.
dis	matrix, pairwise phylogenetic distance matrix.
nworker	integer, for parallel computing. Either a character vector of host names on which to run the worker copies of R, or a positive integer (in which case that number of copies is run on localhost). default is 4, means 4 threads will be run.
memo.size.GB	numeric, to set the memory size as you need, so that calculation of large tree will not be limited by physical memory. unit is Gb. default is 50Gb.
weighted	logic, whether to use abundance-weighted or unweighted metrics. Default is TRUE.
rand	integer, randomization times. default is 1000.
output.bMPD	logic, if TRUE, the output will include beta mean pairwise distance (betaMPD).
sig.index	character, the index for null model significance test. SES or bNRI, standard effect size, i.e. beta net relatedness index (betaNRI); Confidence, percentage of null values less extreme than the observed value, i.e. non-parametric one-side confidence level; RC, modified Raup-Crick index (RC) based on betaMPD, i.e. count the number of null betaMPD lower than observed betaMPD plus a half of the number of null betaMPD equal to observed betaMPD, to get alpha, then calculate betaMPD-based RC as (2 x alpha - 1). default is SES. If input a vector, only the first element will be used.
unit.sum	NULL or a number or a nemeric vector. When a beta diversity index is calculated for a bin, the taxa abundances will be divided by unit.sum to calculate the relative abundances. Usually, unit.sum can be set as the sequencing depth in each sample. Default setting is NULL, means not to do this transformation.
correct.special	logic, whether to correct the special cases. Default is FALSE.
detail.null	logic, if TRUE, the output will include all the null values. Default is FALSE.
special.method	When correct.special is TRUE, which method will be used to check underestimation of deterministic pattern(s) in special cases. MPD, use null model test based on mean pairwise distance; MNTD, use null model test of mean nearest taxon distance; both, use null model test of both MPD and MNTD. Default is MPD.
ses.cut	numeric, the cutoff of significant standard effect size, default is 1.96.
rc.cut	numeric, the cutoff of significant modified Raup-Crick metric, default is 0.95.
conf.cut	numeric, the cutoff of significant one-side confidence level, default is 0.975.
dirichlet	Logic. If TRUE, the taxonomic null model for correcting special cases will use Dirichlet distribution to generate relative abundances in randomized community matrix. default is FALSE.

Details

The beta net relatedness index (betaNRI; Webb et al. 2008, Stegen et al. 2012) is a standardized measure of the mean pairwise distance between samples/communities (betaMPD). Parallel computing is used to improve the speed.

The null model algorithm is "taxa shuffle" (Kembel 2009), i.e. shuffling taxa labels across the tips of the phylogenetic tree to randomize phylogenetic relationships among species.

In the output of beta NRI, the diagonal are set as zero. If the randomized results are all the same, the standard deviation will be zero and betaNRI will be NAN. In this case, beta NRI will be set as zero, since the observed result is not differentiable from randomized results.

Modified RC (Chase et al 2011) and Confidence (Ning et al 2020) are alternative significance test indexes to evaluate how the observed beta diversity index deviates from null expectation, which could be a better metric than standardized effect size (betaNRI) in some cases, e.g. null values do not follow normal distribution.

Value

Output is a list with following elements:

index	a square matrix of betaNRI (or RC or Confidence based on betaMPD) values.
sig.index	character, indicates the index for null model significance test, SES (i.e. betaNRI), RC, or Confidence.
betaMPD.obs	Output only if output.bMPD is TRUE. A square matrix of observed beta MPD values.
rand	Output only if detail.null is TRUE. A matrix with null values of beta MPD for each turnover.
special.crct	Output only if detail.null is TRUE. it will be NULL if correct.special is FALSE. Otherwise, it will be a list with three elements, corresponding to three different null model significance testing indexes, i.e. SES, RC, and Confidence. Each element is a square matrix, where the value is zero if the result for a turnover does not need to correct, otherwise there will be a corrected value.

Note

Version 5: 2021.4.18, fix the bug when detail.null=TRUE and comm has only two samples. Version 4: 2020.8.18, update help document, add example. Version 3: 2020.8.1, change RC opiton to sig.index, add detail.null and conf.cut. Version 2: 2018.10.3, correct special cases Version 1: 2016.3.26.

Author(s)

Daliang Ning

References

Webb, C.O., Ackerly, D.D. & Kembel, S.W. (2008). Phylocom: software for the analysis of phylogenetic community structure and trait evolution. Bioinformatics, 24, 2098-2100.

Kembel, S.W. (2009). Disentangling niche and neutral influences on community assembly: assessing the performance of community phylogenetic structure tests. Ecol Lett, 12, 949-960.

Stegen, J.C., Lin, X., Konopka, A.E. & Fredrickson, J.K. (2012). Stochastic and deterministic assembly processes in subsurface microbial communities. Isme Journal, 6, 1653-1664.

Chase, J.M., Kraft, N.J.B., Smith, K.G., Vellend, M. & Inouye, B.D. (2011). Using null models to disentangle variation in community dissimilarity from variation in alpha-diversity. Ecosphere, 2, 1-11.

Ning, D., Yuan, M., Wu, L., Zhang, Y., Guo, X., Zhou, X. et al. (2020). A quantitative framework reveals ecological drivers of grassland microbial community assembly in response to warming. Nature Communications, 11, 4717.

See Also

bmpd, bNRI.cm

Examples

data("example.data")
comm=example.data$comm
pd=example.data$pd
nworker=2 # parallel computing thread number
rand.time=4 # usually use 1000 for real data.
bNRI=bNRIn.p(comm=comm, dis=pd, nworker = nworker, memo.size.GB = 50,
             weighted = TRUE, rand = rand.time, output.bMPD = FALSE, 
             sig.index = "SES", unit.sum = NULL, correct.special = TRUE,
             detail.null = FALSE, special.method = "MPD")

iCAMP documentation built on June 1, 2022, 9:08 a.m.