STS_sortingcost: A cost computation function for Side-to-Side (STS) algorithm
In JinmiaoChenLab/uSORT: uSORT: A self-refining ordering pipeline for gene selection
Description
Usage
Arguments
Value
Examples
Description
A cost computation function for Side-to-Side (STS) algorithm
Usage
1
2
STS_sortingcost(expr = NULL, method = c("Euclidean", "Correlation",
"eJaccard", "none"))
Arguments
expr
An expresssion matrix containing n-rows of cells and m-cols of genes.
method
A character string indicating the distance function.
Value
A numeric value of sorting cost.
Examples
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10
set.seed(15)
da <- iris[sample(150, 150, replace = FALSE), ]
d <- da[,1:4]
randomOrdering_cost <- STS_sortingcost(d, method= 'Euclidean')
randomOrdering_cost
da <- iris
d <- da[,1:4]
properOrdering_cost <- STS_sortingcost(d, method= 'Euclidean')
properOrdering_cost
JinmiaoChenLab/uSORT documentation built on May 7, 2019, 10:53 a.m.
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Description Usage Arguments Value Examples
Description
A cost computation function for Side-to-Side (STS) algorithm
Usage
1 2 | STS_sortingcost(expr = NULL, method = c("Euclidean", "Correlation",
"eJaccard", "none"))
|
Arguments
expr |
An expresssion matrix containing n-rows of cells and m-cols of genes. |
method |
A character string indicating the distance function. |
Value
A numeric value of sorting cost.
Examples
1 2 3 4 5 6 7 8 9 10 | set.seed(15)
da <- iris[sample(150, 150, replace = FALSE), ]
d <- da[,1:4]
randomOrdering_cost <- STS_sortingcost(d, method= 'Euclidean')
randomOrdering_cost
da <- iris
d <- da[,1:4]
properOrdering_cost <- STS_sortingcost(d, method= 'Euclidean')
properOrdering_cost
|
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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