varCluster | R Documentation |
From data on the observed mutational status of single cells at a
number of genomic sites, computes a likely phylogenetic tree using
PhISCS (https://github.com/sfu-compbio/PhISCS) and associates
single cells with leaves of the tree. The function
clusterMetaclones
should be called on the output in
order to group mutations into clones using a likelihood-based
approach.
varCluster(
mutcalls,
fn = 0.1,
fp = 0.02,
cores = 1,
time = 10000,
tempfolder = tempdir(),
python_env = "",
force_recalc = FALSE,
method = "SCITE"
)
mutcalls |
object of class |
fn |
false negative rate, i.e. the probability of only observing the reference allele if there is a mutation. #add gene-wise |
fp |
false positive, i.e. the probability of observing the mutant allele if there is no mutation. |
cores |
number of cores to use for PhISCS (defaults to 1) |
time |
maximum time to be used for PhISCS optimization, in seconds (defaults to 10000) |
tempfolder |
temporary folder to use for PhISCS output |
python_env |
Any shell commands to execute in order to make the
gurobi python package available. The easiest solution is
running R from an environment where the gurobi python package
is avaiable. In some settings (e.g. RStudio Server), this
parameter can be used instead. |
force_recalc |
Rerun PhISCS even if the |
method |
A string variable of either PhISCS or SCITE depending on the tree-inferring software the user wants to use. Default: PhISCS |
an object of class mutationCalls
, with an
inferred tree structure and cell to clone assignment added.
load(system.file("extdata/LudwigFig7.Rda",package =
"mitoClone2"))
LudwigFig7 <- varCluster(LudwigFig7,
python_env = "",method='SCITE')
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.