Description Usage Arguments Value Author(s) References Examples
Given a set of mutations, ExPANdS predicts the number of clonal expansions in a tumor, the size of the resulting subpopulations in the tumor bulk and which mutations accumulate in a cell prior to its clonal expansion. Input-parameters SNV and CBS hold the paths to tab-delimited files containing the point mutations and the copy numbers respectively. Alternatively SNV and CBS can be read into the workspace and passed to runExPANdS
as numeric matrices. The robustness of the subpopulation predictions by ExPANdS increases with the number of mutations provided. It is recommended that SNV contains at least 200 point mutations to obtain stable results.
1 2 | runExPANdS(SNV, CBS, maxS=0.7, max_PM=6, min_CF=0.1, p=NA, ploidy=2,
nc=1, plotF=2, snvF=NULL, maxN=8000, region=NA, verbose=T)
|
SNV |
Matrix in which each row corresponds to a point mutation. Only mutations located on autosomes should be included. Columns in SNV must be labeled and must include: |
CBS |
Matrix in which each row corresponds to a copy number segment. CBS is typically the output of a circular binary segmentation algorithm. Columns in CBS must be labeled and must include: |
maxS |
Upper threshold for the noise score of subpopulation detection. Only subpopulations identified at a score below maxS are kept. |
max_PM |
Upper threshold for the number of amplicons per mutated cell. Increasing the value of this variable is not recommended unless extensive depth and breadth of coverage underlie the measurements of copy numbers and allele frequencies. See also |
min_CF |
Lower boundary for the cellular prevalence interval of a mutated cell. Mutations for which allele frequency * copy number are below min_{CellFreq}, are excluded from further computation. Decreasing the value of this variable is not recommended unless extensive depth and breadth of coverage underlie the measurements of copy numbers and allele frequencies. |
p |
Precision with which subpopulation size is predicted, a small value reflects a high resolution and can lead to a higher number of predicted subpopulations. |
plotF |
Option for displaying a visual representation of the identified subpopulations (0 - no display; 1 - display subpopulation size; 2 - display subpopulation size and phylogeny). |
snvF |
Prefix of file to which predicted subpopulation composition will be saved. Default: the name of the file from which mutations have been read or "out.expands" if input mutations are not handed over as file path. |
maxN |
Upper limit for number of point mutations used during clustering. If number of user supplied point mutations exceeds maxN, the clustering of cellular frequency distributions will be restricted to point mutations found within region. |
region |
Regional boundary for mutations included during clustering.
Matrix in which each row corresponds to a genomic segment. Columns must include: |
ploidy |
The background ploidy of the sequenced sample (default: 2). Changing the value of this parameter is not recommended. Dealing with cell lines or tumor biopsies of very high (>=0.95) tumor purity is a necessary but not sufficient condition to change the value of this parameter. |
nc |
The number of nodes to be forked to run R in parallel. |
verbose |
Give a more verbose output. |
List with fields:
finalSPs |
Matrix of predicted subpopulations. Each row corresponds to a subpopulation and each column contains information about that subpopulation, such as the size in the sequenced tumor bulk (column Mean Weighted) and the noise score at which the subpopulation has been detected (column score). |
dm |
Matrix containing the input mutations with at least seven additional columns: |
densities |
Matrix as obtained by |
sp_cbs |
Matrix as obtained by |
tree |
An object of class "phylo" (library ape) as obtained by |
Noemi Andor
Noemi Andor, Julie Harness, Sabine Mueller, Hans Werner Mewes and Claudia Petritsch. (2013) ExPANdS: Expanding Ploidy and Allele Frequency on Nested Subpopulations. Bioinformatics.
1 2 3 4 5 |
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