View source: R/VDJ_diversity.R
VDJ_diversity | R Documentation |
Calculates and plots common diversity and overlap measures for repertoires and alike. Requires the vegan package
VDJ_diversity( VDJ, feature.columns, grouping.column, metric, VDJ.VJ.1chain, subsample.to.same.n )
VDJ |
VDJ dataframe output from the VDJ_GEX_matrix function. |
feature.columns |
Character vector. One or more column names from the VDJ of which diversity or overlap metrics are calculated. if more than one column is provided (e.g. c("VDJ_cdr3s_aa","VJ_cdr3s_aa")) these columns will be pasted together before metric calculation. |
grouping.column |
Character. Column name of a column to group metrics by. This could be "sample_id" to calculate the metric for each sample. This column is required if metric = "simpson". If so, the simpson overlap index will be calculated pairwise for all combinations of elements in the grouping.column. Defaults to "none". |
metric |
Character. Diversity or overlap metric to calculate. Can be c("richness", "bergerparker", "simpson", "ginisimpson", "shannon", "shannonevenness", "jaccard"). Defaults to "shannon". If jaccard is selected, a heatmap with the pairwise comparisons between all groups is returned. If any of the others is selected, a dotplot is returned |
VDJ.VJ.1chain |
Boolean defaults to TRUE. Whether to filter out aberrant cells (more than 1 VDJ or VJ chain). |
subsample.to.same.n |
Boolean defaults to TRUE. Whether to subsample larger groups down to the size of the smallest group |
Returns a ggplot with the calculated metric for each group (if provided).
#Calculate shannon index for VDJ CDR3s by sample plot <- VDJ_diversity(VDJ = Platypus::small_vgm[[1]], ,feature.columns = c("VDJ_cdr3s_aa"), grouping.column = "sample_id" ,metric = "shannon") #Calculate Gini-simpson and Simpson index for VDJ and VJ CDR3s by sample VDJ_diversity(VDJ = Platypus::small_vgm[[1]], ,feature.columns = c("VDJ_cdr3s_aa","VJ_cdr3s_aa"), grouping.column = "sample_id" ,metric = "ginisimpson") #Calculate Jaccard index of J gene usage between two samples VDJ_diversity(VDJ = Platypus::small_vgm[[1]], ,feature.columns = c("VDJ_jgene"), grouping.column = "sample_id" ,metric = "jaccard")
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