Description Usage Arguments Value Examples
landmark_designation clusters cells and determines landmark clusters
| 1 2 3 | landmark_designation(rpkmFile, baseName, sampleFile, distMethod = "euclidean",
  method = "kmeans", numcluster = NULL, diversity_cut = 0.6,
  size_cut = 0.05, saveRes = TRUE)
 | 
| 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 | 
a dataframe of two columns, the first column is cell ID, the second column is the landmark cluster the cell belongs to
| 1 2 3 4 5 6 7 8 9 10 11 12 | ## 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)
 | 
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