findOptimalK: Finding optimal number of clusters

In dyohanne/RepAn: Differential abundance Analysis for deep sequenced immune repertoire (Repseq) datasets

Finding optimal number of clusters

Description

Finds optimal k as the average optimal k detected from the within sample clustering of selected repertoire samples.

Usage

findOptimalK(repSeqObj, nSamEval = 2, clusterby, minCSizePerc = 0.1,
  minNClonesPerCluster = 20, kmerWidth = 4, posWt = T,
  distMethod = "euclidean")

Arguments

repSeqObj	is an object containing all repertoire sample data
posWt	boolean to give weights to kmer frequencies depending on their position in the CDR3
distMethod	the distance method used for determining distance between CDR3 feature vectors, default "euclidean"

Value

returns an optimal k for dividing unsupervised clustering results into k compact clusters.

dyohanne/RepAn documentation built on Feb. 3, 2023, 2:41 p.m.