sequences.distance: Dissimilarity/distance indices for sequence data
In bcRep: Advanced Analysis of B Cell Receptor Repertoire Data

Description Usage Arguments Details Value Author(s) References See Also Examples

This function calculates different dissmilarity/distance indices of sequences.

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sequences.distance(sequences = NULL, groups = NULL, 
     method = c("levenshtein", "cosine", "q-gram", "jaccard", "ja-wi", 
                "dam-le", "hamming", "osa", "lcs"), divLength = FALSE)

`sequences`	Vector containing sequences
`groups`	Vector containing names of different samples (if present)
`method`	Dissmilariy method (see details)
`divLength`	Divide sequences into subsets of the same sequence length? (default: FALSE)

This function calculates dissmiliarity/distance indices based on sequences. Levenshtein, cosine, q-gram, Jaccard, Jaro-Winker (ja-wi), Damerau-Levenshtein (dam-le), Hamming, Optimal string alignment (osa) and longest common substring (lcs) distance can be chosen. For details see stringdist-metrics.

Output is a distance matrix containing dissimilarity indices/distances between sequences.

Julia Bischof

van der Loo M (2014). The stringdist package for approximate string matching. The R Journal, 6, pp. 111-122. https://CRAN.R-project.org/package=stringdist

dist.PCoA, plotDistPCoA, geneUsage.distance

## Not run: 
data(clones.ind)
data(clones.allind)
dist1<-sequences.distance(sequences = clones.ind$unique_CDR3_sequences_AA, 
     method = "levenshtein", divLength=TRUE)
dist2<-sequences.distance(sequences = clones.allind$unique_CDR3_sequences_AA, 
     groups = clones.allind$individuals, method = "cosine", divLength=FALSE)

## End(Not run)