icamp.bins: Summarize iCAMP result in each bin

View source: R/icamp.bins.r

icamp.binsR Documentation

Summarize iCAMP result in each bin

Description

This function is to calculate various statistic index to assess relative importance of each process in each bin and each turnover, and bin's contribution to each process.

Usage

icamp.bins(icamp.detail, treat = NULL, clas = NULL, silent = FALSE,
          boot = FALSE, rand.time = 1000, between.group = FALSE)

Arguments

icamp.detail

list object, the output or the "detail" element of the output from icamp.big

treat

matrix or data.frame, indicating the group or treatment of each sample, rownames are sample IDs. Allow to input multi-column matrix, different columns represent different ways to group the samples.

clas

matrix or data.frame, the classification information of species (OTUs).

silent

Logic, whether to show messages. Default is FALSE, thus all messages will be showed.

boot

Logic, whether to do bootstrapping test to get significance of dominating process in each bin.

rand.time

integer, bootstrapping times.

between.group

Logic, whether to analyze between-treatment turnovers.

Details

Bin level analysis can provide insights into community assembly mechanisms. This function provides more detailed statistics with the output of the main function icamp.big.

Value

Output is a list object.

Wtuvk

The dominant process in each turnover of each bin.

Ptuv

Relative importance of each process in governing the turnovers between each pair of communities (samples).

Ptk

Relative importance of each process in governing the turnovers of each bin among a group of samples.

Pt

Relative importance of each process in governing the turnovers in a group of samples.

BPtk

Bin contribution to each process, measuring the contribution of each bin to the relative importance of each process in the assembly of a group of communities.

BRPtk

Bin relative contribution to each process, measuring the relative contribution of each bin to a certain process.

Binwt

Output if treat is given. Bin relative abundance in each group (treatment) of samples.

Bin.TopClass

Output if clas is given. A matrix showing the bin relative abundance; the top taxon ID, percentage in bin, and classification; the most abundant name at each phylogeny level in the bin.

Class.Bin

Output if clas is given. A matrix showing the bin ID and classification information for each taxon.

Note

Version 3: 2021.1.5, fix the error when a tanoxomy name has unrecognizable character. Version 2: 2020.8.19, update help document, add example. Version 1: 2019.12.11

Author(s)

Daliang Ning

References

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

icamp.big

Examples

data("icamp.out")
data("example.data")
treatment=example.data$treat
classification=example.data$classification
rand.time=20 # usually use 1000 for real data.
icampbin=icamp.bins(icamp.detail = icamp.out, treat = treatment,
                    clas = classification, boot = TRUE,
                    rand.time = rand.time, between.group = TRUE)

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