predict_LDA,codonFreq-method | R Documentation |
Predict taxonomic classifications for sequences in a codonFreq
)
object, using linear discriminants from an lda
) model. Plot
disciminants and predictions.
Plot the distribution of MCUFD values per taxon
## S4 method for signature 'codonFreq' predict_LDA( cFobj, ldaObj, rank = "Phylum", minlen = 600, fname = NA_character_, units = "in", width = 10, height = 7, dpi = 600, norm = FALSE, plot = FALSE, identifier = NA_character_ ) ## S4 method for signature 'list' MCUFD_plot( cFres, type = "bar", n = NA_real_, rank = "Phylum", fname = NA_character_, units = "in", width = 10, height = 7, dpi = 600, save = FALSE )
cFobj |
An object of class |
ldaObj |
Object of class |
rank |
Character, taxonomic rank to be used for categorisation of the CUFD hit sequences. Options are "Domain", "Kingdom", and "Phylum". Default = "Phylum". |
minlen |
Numeric, the minimum length of sequence (in codons) to be included in the analysis. Default = 500. |
fname |
Character, name of figure generated. |
units |
Numeric, units to be used for defining the plot size. Options are "in" (default), "cm", and "mm". |
width |
Numeric, width of the figure (in |
height |
Numeric, height of the figure (in |
dpi |
Numeric, resolution of the figure (default = 600). |
norm |
Logical, should the codon abundances be normalised? If TRUE, codon abundances will be converted to codon bias scores, such that the sum of scores for each amino acid sum to 1. Default = FALSE. |
plot |
Logical, should the enrichment results be plotted? Default = FALSE. |
identifier |
Character, optional group label to be assigned to sequences
in the |
cFres |
List of data frames containing MCUFD results. |
type |
Character, the type of plot to make. Options are "bar" (default) and "line". |
n |
Numeric, the number of top-ranked reference taxa to be plotted per input sequence. Default = 100. |
save |
Logical, should the figure be saved to file? Default = FALSE. |
A ggplot
object.
A ggplot
object.
virusSet <- readSeq(example = TRUE) virusCF <- codonFreq(virusSet) exclCod <- c("ATT", "TGT") LDA_tmp <- LDA( exclude = exclCod, rank = "Phylum", trans = FALSE, propTrain = 1, corCut = 0.95, minlen = 600 ) predLDA <- predict_LDA( virusCF, LDA_tmp, rank = "Phylum", plot = TRUE, minlen = 600, fname = "lda_tmp2", height = 5, width = 7 ) head(sort(table(predLDA$class), decreasing = TRUE)) virusSet <- readSeq(example = TRUE) virusCF <- codonFreq(virusSet) exclCod <- c("ATT", "TGT") MCUFD_tmp <- MCUFD(virusCF, exclude = exclCod, norm = TRUE) MCUFD_plot( cFres = MCUFD_tmp, type = "bar", save = TRUE, fname = "MCUFD_bar_kingdom", n = 100, rank = "Kingdom" )
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