plotQC {SeqSQC} | R Documentation

## Plot the QC results for specific QC steps.

### Description

Plot QC results.

### Usage

    plotQC(seqfile, QCstep = c("MissingRate", "SexCheck", "Inbreeding",
      "IBD", "PCA"), interactive = FALSE, sdcoef = 5, pc1 = "EV1",
      pc2 = "EV2", pairedScatter = FALSE, ...)

### Arguments

`seqfile` | SeqSQC object with QC results.
`QCstep` | which QC step the user want to do plotting. Takes values of `c("MissingRate", "SexCheck", "Inbreeding", "IBD", "PCA")`
`interactive` | whether to generate interactive plot. Recommend to use `interactive = TRUE` if user perform sample QC using an rmarkdown script and output plot to html format.
`sdcoef` | for inbreeding outlier check, how many standard deviation we need for identification of inbreeding outliers. The default is 5.
`pc1` | the eigenvector on x axis for PCA result. The default is "EV1" for eigenvector 1.
`pc2` | the eigenvector on y axis for PCA result. The default is "EV2" for eigenvector 2.
`pairedScatter` | for PCA result, whether to plot the paired scatterplot for the first 4 PC axes.
`...` | Arguments to be passed to other methods.

### Value

the ggplot or interactive plot (if output is in html format) for specific QC result. If "interactive=FALSE", it returns a ggplot and author could have the flexibility to add on any layers, scales, faceting specifications and coordinate systems.

### Author(s)

Qian Liu qliu7@buffalo.edu

### Examples

    load(system.file("extdata", "example.seqfile.Rdata", package="SeqSQC"))
    gfile <- system.file("extdata", "example.gds", package="SeqSQC")
    seqfile <- SeqSQC(gdsfile = gfile, QCresult = QCresult(seqfile))
    p <- plotQC(seqfile, QCstep="PCA", interactive=FALSE)
    p

[Package SeqSQC version 1.6.0 Index]