apply_row_deviation: Apply row-wise deviation on the inferred GRN
In RGBM: LS-TreeBoost and LAD-TreeBoost for Gene Regulatory Network Reconstruction
View source: R/proposed_steps.R
apply_row_deviation R Documentation
Apply row-wise deviation on the inferred GRN
Description
This function performs a row-wise standard deviation of network A to generate an S1 matrix which is then used to modify the weights in network A
Usage
apply_row_deviation(A,Ntfs,Ntargets)
Arguments
A
Inferred GRN in the form of Ntfs-by-Ntargets matrix
Ntfs
Total number of transcription factors used in the experiment.
Ntargets
Total number of target genes used in the experiment
Value
Refined adjacency matrix A in the form of Ntfs-by-Ntargets matrix
Author(s)
Raghvendra Mall <rmall@hbku.edu.qa>
RGBM documentation built on April 14, 2023, 9:10 a.m.
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View source: R/proposed_steps.R
| apply_row_deviation | R Documentation |
Apply row-wise deviation on the inferred GRN
Description
This function performs a row-wise standard deviation of network A to generate an S1 matrix which is then used to modify the weights in network A
Usage
apply_row_deviation(A,Ntfs,Ntargets)
Arguments
A |
Inferred GRN in the form of Ntfs-by-Ntargets matrix |
Ntfs |
Total number of transcription factors used in the experiment. |
Ntargets |
Total number of target genes used in the experiment |
Value
Refined adjacency matrix A in the form of Ntfs-by-Ntargets matrix
Author(s)
Raghvendra Mall <rmall@hbku.edu.qa>
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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