# msc.richness: Minicircle Sequence Cluster richness In rKOMICS: Minicircle Sequence Cluster (MSC) Analyses

## Description

The msc.richness function counts how many Minicircle Sequence Clusters (MSC) are present per sample across different percent identities.

## Usage

 `1` ```msc.richness(clustmatrices, samples, groups) ```

## Arguments

 `clustmatrices` a list of cluster matrices. `samples` a vector containing the names of the samples. This can include all samples or it can be a subset. `groups` a vector, of equal length as samples, specifying to which group (e.g. species) the samples belong to.

## Value

 `table` a table containing the number of MSC per sample across different percent identities. `plot` a boxplot visualizing previous results.

## Examples

 ``` 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24``` ```require(ggplot2) data(matrices) data(exData) #### run function richness <- msc.richness(matrices, samples = exData\$samples, groups = exData\$species) apply(richness\$table[which(richness\$table\$group=="L. peruviana"),-(1:2)], 2, mean) apply(richness\$table[which(richness\$table\$group=="L. braziliensis"),-(1:2)], 2, mean) apply(richness\$table[which(richness\$table\$group=="hybrid"),-(1:2)], 2, mean) #### visualize results barplot(richness\$table[,"id93"], names.arg = richness\$table[,1], las=2, cex.names=0.4, main="N of MSC at id 93") #### adjust plot richness\$plot + ggtitle("MSC richness across % id") + theme(axis.text.x = element_text(angle=45, hjust=1)) ### show results of subset table(exData\$species) hybrid <- which(exData\$species=="hybrid") # richness.subset <- msc.richness(matrices, samples = exData\$samples[hybrid], # groups = exData\$species[hybrid]) ```

rKOMICS documentation built on July 21, 2021, 5:07 p.m.