NMF: profplot – R documentation

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NMF

profplot

Plotting Expression Profiles

Description

Plotting Expression Profiles

When using NMF for clustering in particular, one looks for strong associations between the basis and a priori known groups of samples. Plotting the profiles may highlight such patterns.

Usage

profplot(x, ...)

  ## Default S3 method:
 profplot(x, y,
    scale = c("none", "max", "c1"), match.names = TRUE,
    legend = TRUE, confint = TRUE, Colv, labels,
    annotation, ..., add = FALSE)

Arguments

`x`	a matrix or an NMF object from which is extracted the mixture coefficient matrix. It is extracted from the best fit if `x` is the results from multiple NMF runs.
`y`	a matrix or an NMF object from which is extracted the mixture coefficient matrix. It is extracted from the best fit if `y` is the results from multiple NMF runs.
`scale`	specifies how the data should be scaled before plotting. If `'none'` or `NA`, then no scaling is applied and the "raw" data is plotted. If `TRUE` or `'max'` then each row of both matrices are normalised with their respective maximum values. If `'c1'`, then each column of both matrix is scaled into proportions (i.e. to sum up to one). Default is `'none'`.
`match.names`	a logical that indicates if the profiles in `y` should be subset and/or re-ordered to match the profile names in `x` (i.e. the rownames). This is attempted only when both `x` and `y` have names.
`legend`	a logical that specifies whether drawing the legend or not, or coordinates specifications passed to argument `x` of `legend`, that specifies the position of the legend.
`confint`	logical that indicates if confidence intervals for the R-squared should be shown in legend.
`Colv`	specifies the way the columns of `x` are ordered before plotting. It is used only when `y` is missing. It can be: a single numeric value, specifying the index of a row of `x`, that is used to order the columns by `x[, order(x[abs(Colv),])]`. Decreasing order is specified with a negative index. an integer vector directly specifying the order itself, in which case the columns are ordered by `x[, Colv]` a factor used to order the columns by `x[, order(Colv)]` and as argument `annotation` if this latter is missing or not `NA`. any other object with a suitable `order` method. The columns are by `x[, order(Colv)]`
`labels`	a character vector containing labels for each sample (i.e. each column of `x`). These are used for labelling the x-axis.
`annotation`	a factor annotating each sample (i.e. each column of `x`). If not missing, a coloured raw is plotted under the x-axis and annotates each sample accordingly. If argument `Colv` is a factor, then it is used to annotate the plot, unless `annotation=NA`.
`...`	graphical parameters passed to `matplot` or `matpoints`.
`add`	logical that indicates if the plot should be added as points to a previous plot

Details

The function can also be used to compare the profiles from two NMF models or mixture coefficient matrices. In this case, it draws a scatter plot of the paired profiles.

Examples

# create a random target matrix
v <- rmatrix(40, 10)

# fit a single NMF model
res <- nmf(v, 3)
profplot(res)

# fit a multi-run NMF model
res2 <- nmf(v, 3, nrun=2)
# ordering according to first profile
profplot(res2, Colv=1) # increasing

# draw a profile correlation plot: this show how the basis components are
# returned in an unpredictable order
profplot(res, res2)

# looking at all the correlations allow to order the components in a "common" order
profcor(res, res2)

NMF

Algorithms and Framework for Nonnegative Matrix Factorization (NMF)

v0.23.0

GPL (>= 2)

Authors

Renaud Gaujoux, Cathal Seoighe

Initial release

2020-07-30