corrs2Gene: Examine Correlations to a Specific Gene in a Datamatrix

In axm323/dataVisEasy: datavisEasy: Data visualizations Using Annotations Made Easy

Examine Correlations to a Specific Gene in a Datamatrix

Description

Provides a quick way to check for correlations to a specific gene in a given data matrix. If no limits are supplied, will return a histogram of all gene correlations to the gene in question. When limits are supplied, acts as a wrapper for myHeatmap() where a heatmap is returned including all genes with corrleations that are more negatively correlated than the lower limit and more positively correlated than the upper limit.

Usage

corrs2Gene(data, gene, limits = NULL, method = "pearson", linkage = "complete",
  NA.handling = "pairwise.complete.obs", nbreaks = 20, show.report = F, clust.rows = T,
  clust.cols = T, row.groups = NA, col.groups = NA, gaps.row = NULL, gaps.col = NULL,
  gap.width = 1, order.by.gene = NULL, order.by.sample = NULL, cell.width = NA,
  cell.height = NA, fontsize.row = 10, fontsize.col = 10, show.rownames = T,
  show.colnames = F, treeheight.row = 20, treeheight.col = 20, hide.plot = FALSE,
  na.fix = FALSE, na.offset = 2, show.legend = TRUE, show.annotations = TRUE,
  is.raw.Ct = FALSE, drop.annot.levels = TRUE)

Arguments

data	numeric data matrix with samples/observations in the columns and genes/variables in the rows
gene	name of gene to which all other genes will be correlated with
limits	vector of two numbers, giving the lower and upper bounds of the returned correlations. If NULL (the default) will return a histogram of all correlations to the gene in question. When limits are provided, correlations below the lower limit and above the upper limit will be displayed in a heatmap.
method	method to be used to calculate correlations. Accepts values to be passed to cor() such as "pearson" (default), "spearman", and "kendall".
linkage	linkage clustering method used for clustering and to be passed to hclust(). Accepts all methods accepted by hclust()
NA.handling	how missing values should be handled in the case of correlations, passed to the "use" argument of cor()
nbreaks	number of breaks for histogram when limits are NULL
show.report	If TRUE, will return correlations to the gene of interest based on the limits provided

additional arguments passed to myHeatmap

clust.rows	should rows be clustered, default = TRUE. When TRUE, rows will be clustered within each annotation
clust.cols	should columns be clustered, default = TRUE. When TRUE, columns will be clustered within each annotation
row.groups	numeric to be passed to cutree(). Will split the dendrogram into the number of groups indicated. Only usable if groupings.genes is not provided
col.groups	numeric to be passed to cutree(). Will split the dendrogram into the number of groups indicated. Only usable if groupings is set to FALSE
gaps.row	numeric vector specifying gaps to be inserted into rows of the data, only works if clust.rows = FALSE
gaps.col	numeric vector specifying gaps to be inserted into columns of the data, only works if clust.cols = FALSE
gap.width	numeric indicating the width of gaps along both rows and columns. Works in tandem with both gaps.row.spec/gaps.col.spec and groupings.gaps/groupings.genes.gaps where the indicated gaps from the previous arguments will be widened by the factor indicated.
order.by.gene	optional character equal to one of the rownames of the data to order the columns of the data by increasing levels of indicated row. If groupings is supplied, each group of the annotations will be ordered by the supplied gene.
order.by.sample	optional character equal to one of the colnames of the data to order the rows of the data by increasing levels of indicated column. If groupings.genes is supplied, each group of the row annotaitons will be ordered by the supplied sample
cell.width	individual cell width in points. If left as NA, then the values depend on the size of plotting window.
cell.height	individual cell height in points. If left as NA, then the values depend on the size of plotting window.
fontsize.row	size of font for row names
fontsize.col	size of font for column names
show.rownames	logical value determining if rownames should be displayed, default = TRUE
show.colnames	logical value determining if colnames should be displayed, default = FALSE
treeheight.row	the height of a dendrogram tree for rows, if these are clustered. Default value 20 points
treeheight.col	the height of a dendrogram tree for columns if these are clustered. Default value 20 points.
hide.plot	should the plot be displayed
na.fix	logical: should missing values be treated as NA or be set to a low value (see na.offset). Values will still be colored gray in heatmap but may aid in clustering when many missing values are present.
na.offset	option to treat missing/NA values as an offset from the minimum value. Ex a value of 2 will set missing values to min(data) - 2. Values will still be colored gray in heatmap but may aid in clustering when many missing values are present.
show.legend	logical, should legend be shown
show.annotations	logical, should annotation legend be shown
is.raw.Ct	logical. If set to TRUE, will reverse the scale of the data to indicate low values as high expression as in the case of raw Ct values from qPCR, in this case, missing values will also be set to a high value to reflect low expression level
drop.annot.levels	logial, should annotations not included in the output heatmap be shown in the annotation legend.

Value

If limits are NULL returns a plot histogram. If limits are provided, returns a pheatmap object, see myHeatmap

Author(s)

~~Alison Moss~~

See Also

See Also as myHeatmap

Examples

##initiate parameters
initiate_params()


##View range of correlations with gene of interest as histogram
corrs2Gene(RAGP_norm, gene = "NeuN")

##provide limits to show heatmap of genes with negative correlations below/above lower/upper limit
corrs2Gene(RAGP_norm, gene = "NeuN", limits = c(-0.4, 0.5))
corrs2Gene(RAGP_norm, "NeuN", c(-0.4, 0.5), order.by.gene = "NeuN")

##return list of correlations passing provided limits
corrs2Gene(RAGP_norm, "NeuN", c(-0.4, 0.5), show.report = TRUE)

axm323/dataVisEasy documentation built on Feb. 1, 2024, 11:53 p.m.