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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