Sequencing and microarray samples often are collected or processed in multiple batches or at different times. This often produces technical biases that can lead to incorrect results in the downstream analysis. BatchQC is a software tool that streamlines batch preprocessing and evaluation by providing interactive diagnostics, visualizations, and statistical analyses to explore the extent to which batch variation impacts the data. BatchQC diagnostics help determine whether batch adjustment needs to be done, and how correction should be applied before proceeding with a downstream analysis. Moreover, BatchQC interactively applies multiple common batch effect approaches to the data, and the user can quickly see the benefits of each method. BatchQC is developed as a Shiny App. The output is organized into multiple tabs, and each tab features an important part of the batch effect analysis and visualization of the data. The BatchQC interface has the following analysis groups: Summary, Differential Expression, Median Correlations, Heatmaps, Circular Dendrogram, PCA Analysis, Shape, ComBat and SVA.
|Author||Solaiappan Manimaran <email@example.com>, W. Evan Johnson <firstname.lastname@example.org>, Heather Selby <email@example.com>, Claire Ruberman <firstname.lastname@example.org>, Kwame Okrah <email@example.com>, Hector Corrada Bravo <firstname.lastname@example.org>|
|Date of publication||None|
|Maintainer||Solaiappan Manimaran <email@example.com>|
|License||GPL (>= 2)|
batchQC: Checks for presence of batch effect and creates a html report...
batchQC_analyze: Checks for presence of batch effect and reports whether the...
batchqc_circosplot: Produce Circos plot
batchQC_condition_adjusted: Returns adjusted data after remove the variation across...
batchqc_correlation: Produce correlation heatmap plot
batchqc_corscatter: Produce Median Correlation plot
batchqc_explained_variation: Returns a list of explained variation by batch and condition...
batchQC_filter_genes: Returns a datset after filtering genes of zero variance...
batchQC_fsva_adjusted: Use frozen surrogate variable analysis to remove the...
batchqc_heatmap: Produce heatmap plots for the given data
batchQC_num.sv: Returns the number of surrogate variables to estimate in the...
BatchQCout-class: The BatchQC output class to output BatchQC results
batchqc_pca: Performs principal component analysis and produces plot of...
batchqc_pca_svd: Performs PCA svd variance decomposition and produces plot of...
batchqc_pc_explained_variation: Returns explained variation for each principal components
batchQC_shapeVariation: Perform Mean and Variance batch variation analysis
batchQC_sva: Estimate the surrogate variables using the 2 step approach...
batchQC_svregress_adjusted: Regress the surrogate variables out of the expression data
batchtest: Performs test to check whether batch needs to be adjusted
combatPlot: Adjust for batch effects using an empirical Bayes framework...
example_batchqc_data: Batch and Condition indicator for signature data captured...
getShinyInput: Getter function to get the shinyInput option
getShinyInputCombat: Getter function to get the shinyInputCombat option
getShinyInputOrig: Getter function to get the shinyInputOrig option
getShinyInputSVA: Getter function to get the shinyInputSVA option
getShinyInputSVAf: Getter function to get the shinyInputSVAf option
getShinyInputSVAr: Getter function to get the shinyInputSVAr option
gnormalize: Perform Genewise Normalization of the given data matrix
log2CPM: Compute log2(counts per mil reads) and library size for each...
makeSVD: Compute singular value decomposition
pcRes: Compute variance of each principal component and how they...
plotPC: Plot first 2 principal components
protein_example_data: Batch and Condition indicator for protein expression data
rnaseq_sim: Generate simulated count data with batch effects for ngenes
setShinyInput: Setter function to set the shinyInput option
setShinyInputCombat: Setter function to set the shinyInputCombat option
setShinyInputOrig: Setter function to set the shinyInputOrig option
setShinyInputSVA: Setter function to set the shinyInputSVA option
setShinyInputSVAf: Setter function to set the shinyInputSVAf option
setShinyInputSVAr: Setter function to set the shinyInputSVAr option