performVGWAS: Perform voxelwise genome-wide association study.
In JakubBartoszewicz/RImaGen: Fast Voxelwise Genome-Wide Association Studies in R

Loads and prepares the data, runs preliminary (if necessary) and full analyses. Then visualises the results.

performVGWAS(genePath, niiFiles, niiIDs, ref.imgPath, maskPath, subFactor,
  top.range, covar = character(), errorCovariance = numeric(),
  out.subFactor = subFactor, matPath = NULL, outPath = NULL,
  force.snps = NULL, useModel = MatrixEQTL::modelLINEAR, log.cutoff = 4,
  eff.no.tests = 275575, sampleSize = NULL, randomSample = FALSE,
  visualise = TRUE, saveNIfTI = TRUE, uncut = TRUE,
  mockPath.flatROIs = NULL, mockPath.pre = NULL)

`genePath`	Path to a directory containing plink files with genomic data.
`niiFiles`	Paths to files containing imaging data.
`niiIDs`	Subject IDs for each image. Shuffle for permutation tests.
`ref.imgPath`	Path to a referance image.
`maskPath`	Path to an image mask.
`subFactor`	Downsampling factor.
`top.range`	Range of top SNPs to be analysed and visualised.
`covar`	Covariates matrix with subject IDs as column names.
`errorCovariance`	Covariance matrix for the error term. Set to `numeric()` for multiple of identity (default, most cases).
`out.subFactor`	Output images downsampling factor. Default: equal to `subFactor`.
`matPath`	Path to convolution matrix for coregistration of results to the reference image. Set to `NULL` if in the same space.
`outPath`	Path to output directory.
`force.snps`	`character` vector of SNPs forced to be analysed even if not passing the quality control.
`useModel`	Regression model to use.
`log.cutoff`	Negative log p-value cutoff value for results visualisation.
`eff.no.tests`	Effective number of tests (SNPs) for p-value correction.
`sampleSize`	Subject sample size.
`randomSample`	`logical`. Set to `TRUE` for subject sample randomisation.
`visualise`	`logical`. Set to `FALSE` to disable results visualisation for bigger analyses.
`saveNIfTI`	`logical`. Set to `FALSE` to disable saving nifti results for bigger analyses.
`uncut`	`logical`. Set to `FALSE` to disable full maps generation.
`mockPath.flatROIs`	Path to input file with saved flatROIs object for vGWAS mocking. Mock parameters should match original parameters. Useful for registering results to different standard spaces and resolutions, selecting alternative SNPs for the full analysys, of using different genetic models.
`mockPath.pre`	Path to input file with saved preliminary analysis results object for vGWAS mocking. Mock parameters should match original parameters. Useful for registering results to different standard spaces and resolutions, selecting alternative SNPs for the full analysis, or using different genetic models. `NULL` for real analyses.