landmark_designation: landmark_designation clusters cells and determines landmark...

In dynverse/Mpath: Mpath: a single-cell RNAseq data analysis algorithm that maps multi-branching single-cell trajectories revealing cell progression during development

Description

landmark_designation clusters cells and determines landmark clusters

Usage

landmark_designation(rpkmFile, baseName, sampleFile, distMethod = "euclidean",
  method = "kmeans", numcluster = NULL, diversity_cut = 0.6,
  size_cut = 0.05, saveRes = TRUE)

Arguments

rpkmFile	a tab delimited txt file of expression data, containing cells in columns and genes in rows
baseName	a character string indicating of prefix name of resulting files
sampleFile	a tab delimited txt file of sample annotation with two columns, the first column is cell ID, the second column is group ID
distMethod	the method for calculating dissimilarity between cells. distMethod can be one of "pearson", "kendall", "spearman" or "euclidean". Default is "euclidean".
method	method for distinguishing landmark clusters from non-landmark clusters.method can be "kmeans" or "diversity" or "size" or "diversity_size". When method="diversity", numlm needs to be specified. Default is "diversity_size".
numcluster	number of initial clusters
diversity_cut	the cutoff value of diversity for differentiating landmark clusters from non-landmark clusters. The diversity of a landmark cluster must be below this cutoff.
size_cut	the cutoff value of size i.e. number of cells for differentiating landmark clusters from non-landmark clusters. The number of cells in a landmark cluster must be greater than this cutoff.
saveRes	a boolean to indicate whether to save result files

Value

a dataframe of two columns, the first column is cell ID, the second column is the landmark cluster the cell belongs to

Examples

## Not run: 
rpkmFile = "TPM_GSE60783_noOutlier_geneQC0.05anyGroup_CD4vsCD8DEG.txt";
baseName = "TPM_GSE60783_noOutlier_geneQC0.05anyGroup_CD4vsCD8DEG";
sampleFile = "sample_GSE60783_noOutlier.txt";
landmark_cluster <- landmark_designation(rpkmFile = rpkmFile,
                                         baseName = baseName,
                                         sampleFile = sampleFile,
                                         method = "diversity_size",
                                         numcluster = 11, diversity_cut=0.6,
                                         size_cut=0.05)

## End(Not run)

dynverse/Mpath documentation built on May 14, 2019, 8:42 a.m.