PlotGC: Plot GC content.
In mevers/RNAModR: Functional Analysis of RNA Modifications

Description Usage Arguments Details Value Author(s)

Plot and assess the difference in the distributions of GC content within a window around sites from two txLoc objects. See 'Details'.

1 2	PlotGC(txLoc1, txLoc2, flank = 10, norm_region = FALSE, downsample = TRUE, seed = NULL)

`txLoc1`	A `txLoc` object.
`txLoc2`	A `txLoc` object.
`flank`	An `integer` scalar; see 'Details'.
`norm_region`	A `logical` scalar; if `TRUE` normalise the GC content in the window to the GC content of the corresponding transcript region; default is `FALSE`.
`downsample`	A `logical` scalar; if `TRUE`, subsample sites from `txLoc2` to match the number of sites per transcript region from `txLoc1`; default is `TRUE`.
`seed`	A single value, interpreted as an `integer`, or `NULL`; this is to ensure reproducibility when subsampling `txLoc2` sites; ignored when `downsample == FALSE`; default is `NULL`.

The function calculates the GC content within a window around every site from two txLoc objects. The window is defined by extending the position of every txLoc site upstream and downstream by flank nucleotides (if possible). The means of the resulting GC content distributions are assessed using a two-sample two-tailed t-test. If norm_region = TRUE, the GC content in the window is normalised to the GC content of the entire transcript region. If downsample = TRUE, the number of windows/sites from the second txLoc2 object is downsampled to match the number of windows/sites from the txLoc1 object. This is useful (and therefore the default setting) when comparing the GC distribution around positive and null sites, as the list of null sites is often significantly larger than that of the positive sites. Note that this function calls GetGC, which performs the sequence extraction and GC calculation. See ?GetGC for details.