marginalLikelihoodM2: Marginal M2 Calculation
In USCDTG/tLOH: Assessment of evidence for LOH in spatial transcriptomics pre-processed data using Bayes factor calculations
marginalLikelihoodM2 R Documentation
Marginal M2 Calculation
Description
Calculation of the marginal likelihood of Model 2, HET
Arguments
x
Dataframe output by tLOHDataImport
a
Alpha value
b
Beta value
Details
The reference and total counts should come from a .csv output by the spatial LOH pre-processing pipeline.
The recommended values for both Alpha2 and Beta2 is 500.
Value
The value returned from marginalLikelihoodM1 is numeric
Author(s)
Michelle Webb
Examples
test <- data.frame(REF=c(10,2,3,4,5,10),TOTAL=c(20,20,20,20,20,20))
apply(test, MARGIN = 1, FUN = marginalLikelihoodM1, a = 500, b = 500)
USCDTG/tLOH documentation built on Dec. 19, 2024, 10:24 p.m.
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| marginalLikelihoodM2 | R Documentation |
Marginal M2 Calculation
Description
Calculation of the marginal likelihood of Model 2, HET
Arguments
x |
Dataframe output by tLOHDataImport |
a |
Alpha value |
b |
Beta value |
Details
The reference and total counts should come from a .csv output by the spatial LOH pre-processing pipeline. The recommended values for both Alpha2 and Beta2 is 500.
Value
The value returned from marginalLikelihoodM1 is numeric
Author(s)
Michelle Webb
Examples
test <- data.frame(REF=c(10,2,3,4,5,10),TOTAL=c(20,20,20,20,20,20))
apply(test, MARGIN = 1, FUN = marginalLikelihoodM1, a = 500, b = 500)
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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