PreProcess: Pre-processing of mouse data for predictions by FIT
In RachellyN/FIT: Predicts human disease relevant genes from mouse model gene expression, based on prior mouse and human gene expression comparisons
Description
Usage
Arguments
Details
Description
First, the genes are filtered only to those that have slopes in the model.
Usage
1
PreProcess(MouseData, DataType)
Arguments
MouseData
The mouse data.
DataType
'microarray' or 'rnaseq'
Details
Pre-processing for microarrays includes 4 additional steps:
a) Computing fold-change per gene
b) Computing Z-scores per gene
c) Computing Z-tests per gene
d) Merging human orthologs
RachellyN/FIT documentation built on May 16, 2019, 6:59 p.m.
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Description Usage Arguments Details
Description
First, the genes are filtered only to those that have slopes in the model.
Usage
1 | PreProcess(MouseData, DataType)
|
Arguments
MouseData |
The mouse data. |
DataType |
'microarray' or 'rnaseq' |
Details
Pre-processing for microarrays includes 4 additional steps: a) Computing fold-change per gene b) Computing Z-scores per gene c) Computing Z-tests per gene d) Merging human orthologs
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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