sim_par {mina} | R Documentation

## Function for community similarity calculation used by 'tina', modified from https://github.com/defleury/Schmidt_et_al_2016_community_similarity/blob/ master/functions.community_similarity.R

### Description

Function for community similarity calculation used by 'tina', modified from https://github.com/defleury/Schmidt_et_al_2016_community_similarity/blob/ master/functions.community_similarity.R

### Usage

    sim_par(x, y, sim_method = "w_ja", threads = 80, nblocks = 400)

### Arguments

`x` | An quantitative matrix.
`y` | The Cij matrix, which is correlation matrix of adjusted sparcc matrix of x.
`sim_method` | The method for similarity, "w_ja" and "uw_ja" are available for weighted and unweighted Jaccard similarity respectively.
`threads` | The number of threads used for parallel running, 80 by default.
`nblocks` | The number of row / column for splitted sub-matrix, 400 by default.

### Value

s The output similarity matrix.

### Examples

    ## Not run:
    data(maize_asv)
    maize_tab <- maize_asv[1 : 1000, 1 : 200]
    asv <- norm_tab(maize_tab, method = "raref", depth = 100)
    asv[is.na(asv)] <- 0
    asv_sparcc <- sparcc(asv, threads = 8, nblocks = 40)
    tmp.S <- adj(asv_sparcc, method = "spearman")
    y <- 0.5 * (tmp.S + 1)
    s <- sim_par(asv_sparcc, y, sim_method = "w_ja", threads = 8, nblocks = 40)

    ## End(Not run)

[Package mina version 1.2.0 Index]