runSparkx: Identify genes of interest with SPARKX
In kueckelj/SPATA2: A Toolbox for Spatial Gene Expression Analysis
getSparkxGeneDf R Documentation
Identify genes of interest with SPARKX
Description
A wrapper around the algorithm introduced by Zhu et al. 2021
to identify genes with spatial expression pattern with SPARK-X.
Usage
getSparkxGeneDf(object, threshold_pval = 1, arrange_pval = TRUE)
getSparkxGenes(object, threshold_pval)
getSparkxResults(object, test = TRUE)
runSparkx(object, numCores = 1, option = "mixture", verbose = NULL)
Arguments
object
An object of class spata2.
test
Character value. One of any. all, identical, not_identical and
none. Specifies how input for tags is used to select image annotations.
See section Selection of image annotation with tags for more information.
verbose
Logical. If set to TRUE informative messages regarding
the computational progress will be printed.
(Warning messages will always be printed.)
Value
An updated spata object.
Author(s)
Zhu, J., Sun, S. & Zhou, X. SPARK-X: non-parametric modeling enables
scalable and robust detection of spatial expression patterns for large spatial
transcriptomic studies. Genome Biol 22, 184 (2021). https://doi.org/10.1186/s13059-021-02404-0
kueckelj/SPATA2 documentation built on March 16, 2024, 10:25 a.m.
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| getSparkxGeneDf | R Documentation |
Identify genes of interest with SPARKX
Description
A wrapper around the algorithm introduced by Zhu et al. 2021 to identify genes with spatial expression pattern with SPARK-X.
Usage
getSparkxGeneDf(object, threshold_pval = 1, arrange_pval = TRUE)
getSparkxGenes(object, threshold_pval)
getSparkxResults(object, test = TRUE)
runSparkx(object, numCores = 1, option = "mixture", verbose = NULL)
Arguments
object |
An object of class |
test |
Character value. One of any. all, identical, not_identical and
none. Specifies how input for |
verbose |
Logical. If set to TRUE informative messages regarding the computational progress will be printed. (Warning messages will always be printed.) |
Value
An updated spata object.
Author(s)
Zhu, J., Sun, S. & Zhou, X. SPARK-X: non-parametric modeling enables scalable and robust detection of spatial expression patterns for large spatial transcriptomic studies. Genome Biol 22, 184 (2021). https://doi.org/10.1186/s13059-021-02404-0
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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