clusterCells | R Documentation |
Clusters cells according to their copy number profile.
clusterCells(cnps, k=NA, h=NA, weights=NULL, minSegLength=1E6, chrOrder=NULL, HFUN="ward.D2", crit="AIC",...)
cnps |
Segment-by-cell matrix of copy number states (output of |
k |
Desired number of clusters (see also |
h |
Threshold used to define clones from hierarchical clustering result. A subtree is defined as a clone if the maximum distance between its cell members is less than 100*h% of the genome. |
weights |
Vector of weights assigning differential importance to segments (typically calculated based on segment lengths). |
minSegLength |
Minimum number of base pairs below which a segment is to be excluded when defining clones. |
chrOrder |
Specifies order in which chromosomes should be plotted. |
HFUN |
Agglomeration method used to compute the hierarchical clustering (see also |
crit |
Criterion used to opimize number of clusters. |
... |
additional arguments passed on to |
Let CNF be the matrix of copy number states per non-private segment per cell, with entries (i, j) pointing to the copy number state of cell j at locus i.
Pairwise distances between cells are calculated in Hamming space of their segmental copy number profiles (rows in CNF), weighted by segment length. Hierarchical clustering is used to build a tree of the cells from the distance matrix. A subtree is defined as a clone if the maximum distance between its cell members is less than a user-defined fraction of the genome (h).
Alternatively, if k is set, the tree is cut to obtain k clones.
If neither h nor k are set, Akaike information criterion is used to decide on anywhere between 1 and 30 clones.
List with three fields:
cnps |
Segment-by-cell matrix of copy number states. |
sps |
The clone membership of each cell (that is, columns in cnps). |
tree |
An object of class hclust. |
Noemi Andor
Andor, N.*, Lau, B.*, Catalanotti, C., Kumar, V., Sathe, A., Belhocine, K., Wheeler, T., et al. (2018) Joint single cell DNA-Seq and RNA-Seq of gastric cancer reveals subclonal signatures of genomic instability and gene expression. doi: https://doi.org/10.1101/445932
data(cnps) set.seed(3) rcells = sample(colnames(cnps), 120) outc = clusterCells(cnps[apply(cnps, 1, var)>0, rcells])
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