View source: R/clonalOverlap.R
clonalOverlap | R Documentation |
This functions allows for the calculation and visualizations of various overlap metrics for clones. The methods include overlap coefficient (overlap), Morisita's overlap index (morisita), Jaccard index (jaccard), cosine similarity (cosine) or the exact number of clonal overlap (raw).
clonalOverlap(
input.data,
cloneCall = "strict",
method = NULL,
chain = "both",
group.by = NULL,
order.by = NULL,
exportTable = FALSE,
palette = "inferno"
)
input.data |
The product of |
cloneCall |
How to call the clone - VDJC gene (gene), CDR3 nucleotide (nt), CDR3 amino acid (aa), VDJC gene + CDR3 nucleotide (strict) or a custom variable in the data |
method |
The method to calculate the "overlap", "morisita", "jaccard", "cosine" indices or "raw" for the base numbers |
chain |
indicate if both or a specific chain should be used - e.g. "both", "TRA", "TRG", "IGH", "IGL" |
group.by |
The variable to use for grouping |
order.by |
A vector of specific plotting order or "alphanumeric" to plot groups in order |
exportTable |
Returns the data frame used for forming the graph |
palette |
Colors to use in visualization - input any hcl.pals |
The formulas for the indices are as follows:
Overlap Coefficient:
overlap = \frac{\sum \min(a, b)}{\min(\sum a, \sum b)}
Raw Count Overlap:
raw = \sum \min(a, b)
Morisita Index:
morisita = \frac{\sum a b}{(\sum a)(\sum b)}
Jaccard Index:
jaccard = \frac{\sum \min(a, b)}{\sum a + \sum b - \sum \min(a, b)}
Cosine Similarity:
cosine = \frac{\sum a b}{\sqrt{(\sum a^2)(\sum b^2)}}
Where:
a
and b
are the abundances of species i
in groups A and B, respectively.
ggplot of the overlap of clones by group
#Making combined contig data
combined <- combineTCR(contig_list,
samples = c("P17B", "P17L", "P18B", "P18L",
"P19B","P19L", "P20B", "P20L"))
clonalOverlap(combined,
cloneCall = "aa",
method = "jaccard")
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