| testData {DiPALM} | R Documentation |
Test Data: Data for function testing
Description
A list of objects that can be used to test individual DiPALM functions.
Usage
data("testData")Format
A List of 6 objects:
$timeCourseList - A List of 4 matrices containing mRNA expression data on Brassica rapa R500.
$Drought.R1 (Plants exposed to drought, Replicate 1) A matrix of time-course gene expression data [18428 Genes X 12 Time-points]
$Drought.R2 (Plants exposed to drought, Replicate 2) A matrix of time-course gene expression data [18428 Genes X 12 Time-points]
$Watered.R1 (Properly watered plants, Replicate 1) A matrix of time-course gene expression data [18428 Genes X 12 Time-points]
$Watered.R2 (Properly watered plants, Replicate 2) A matrix of time-course gene expression data [18428 Genes X 12 Time-points]
$moduleEigengenes - A dataframe [12 rows and 90 columns] representing 90 different expression vectors that describe descrete expression patterns found in the whole dataset ($timeCourseList).
Rows: each row represents a single time-point
Columns: each column represents a distinct expression pattern seen repeatedly in the full data
$modelDesign - A matrix [4 rows and 2 columns] used as a design matrix for a simple linear model. This matrix provides a mapping between the input instances (timeCourseList) and the two fixed effects fitted in the mode (Drought and Watered). This matrix was created with
model.matrix.$modelContrast - A character string specifying the contrast to be evaluated using the fitted model for each gene. This example is used to compare watered to drought conditions.
$testResults - A named numeric vector with 18428 values from DiPALM test results on actual data.
names: Gene accessions
values: The summed absolute values of t-values generated from limma model contrasts related to each eigengene pattern. This can be thought of as a DiPALM score for differential patterning.
$permutedResults- A named numeric vector with 18428 values from DiPALM test results on permuted data. This vector acts as a null distribution in order to estimate significance of actual test results.
names: Gene accessions
values: The summed absolute values of t-values generated from limma model contrasts related to each eigengene pattern using permuted expression data. This can be thought of as a null distribution of DiPALM scores for differential patterning.
Source
Data is from: Greenham et al., eLife 2017;6:e29655