Package 'unifiedWMWqPCR'

Title: Unified Wilcoxon-Mann Whitney Test for testing differential expression in qPCR data
Description: This packages implements the unified Wilcoxon-Mann-Whitney Test for qPCR data. This modified test allows for testing differential expression in qPCR data.
Authors: Jan R. De Neve & Joris Meys
Maintainer: Joris Meys <[email protected]>
License: GPL (>=2)
Version: 1.41.0
Built: 2024-07-02 03:01:10 UTC
Source: https://github.com/bioc/unifiedWMWqPCR

Help Index


Unified Wilcoxon-Mann Whitney Test for qPCR data.

Description

This package allows you to carry out the unified Wilcoxon-Mann Whitney Test for qPCR data. If you use this package for research purposes, please cite the following article:

Details

De Neve, Jan; Meys, Joris; Ottoy, Jean-Pierre; Clement, Lieven and Thas, Olivier. "UnifiedWMWqPCR: The unified Wilcoxon-Mann-Whitney test for analyzing RT-qPCR data in R." Bioinformatics(2014): Vol.30, Issue 17, pp.2494-2495.

Or see citation("unifiedWMWqPCR")


S3 method as.matrix for uwmwEstimate objects.

Description

For uwmwEstimate objects, an as.matrix method is defined that transforms the object to a numeric matrix with the following columns:

est:

The estimates

se:

The standard errors on estimates.

ll

lower limit of the confidence interval

ul

upper limit of the confidence interval

The row names are the names of the tested genes/features. The matrix takes the ordering in the object into account if necessary.

Usage

## S3 method for class 'uwmwEstimate'
as.matrix(x, ...)

## S4 method for signature 'uwmwEstimate'
as.matrix(x, ...)

Arguments

x

a uwmwEstimate object

...

currently ignored

Value

A matrix with the columns specified above.

Author(s)

Joris Meys

Examples

data(NBmat)
NBtest <- uWMW(NBmat, groups=NBgroups)
NBest <- getEstimate(NBtest,"p")
as.matrix(NBtest)

S3 method as.matrix for uwmwRes objects.

Description

For uwmwRes objects, an as.matrix method is defined that transforms the object to a numeric matrix with the following columns:

logor:

The log odds ratio values

se:

The standard errors on the log OR values.

or

The odds ratio values

z.value

the z values related to the log OR values

p.value

The p values related to the log OR values

The row names are the names of the tested genes/features. The matrix takes the ordering in the object into account if necessary.

Usage

## S3 method for class 'uwmwRes'
as.matrix(x, ...)

## S4 method for signature 'uwmwRes'
as.matrix(x, ...)

Arguments

x

a uwmwRes object

...

currently ignored

Value

A matrix containing the columns specified above.

Examples

data(NBmat)
NBtest <- uWMW(NBmat, groups=NBgroups)
as.matrix(NBtest)

Making a forest plot of the results of uWMW

Description

This function creates a forest plot indicating the (log) odds ratios, the (log) odds or the probabilities for the results of the unified Wilcoxon-Mann-Whitney test.

Usage

## S4 method for signature 'ANY'
forestplot(x, ...)

## S4 method for signature 'uwmwRes'
forestplot(x, estimate = c("logor", "logodds", "or",
  "odds", "p"), level = 0.95, ...)

## S4 method for signature 'uwmwEstimate'
forestplot(x, ...)

forestplot.internal(x, annotate = TRUE, addfit = TRUE, xlim = NULL,
  alim = NULL, ylim = NULL, at = NULL, steps = 5, level = 0.95,
  digits = 2, refline = NULL, xlab = NULL, slab = NULL, mlab = NULL,
  ilab = NULL, ilab.xpos = NULL, ilab.pos = NULL, order = NULL,
  transf = FALSE, atransf = FALSE, targs = NULL, rows = NULL,
  efac = 1, pch = 15, psize = 1, col = "darkgrey",
  border = "darkgrey", cex = NULL, cex.lab = NULL, cex.axis = NULL,
  refcol = "red", predcol = refcol, ...)

Arguments

x

An object of class uwmwRes or uwmwEstimate.

...

parameters passed down to the internal functions. These can be any of the following.

estimate

An optional character string defining which measure should be plotted. It can take the values logor, or, logodds, odds or p (for displaying the probability of differential expression, not the p-value!). Defaults to logor. Note that this argument is ignored when plotting an uwmwEstimate object.

level

Numerical value between 0 and 1 to specify the width of the confidence interval. Defaults to 0.95 (95% confidence interval).

annotate

A logical value indicating whether the plot needs to be annotated, i.e. whether the values for the chosen measure and confidence interval should be displayed on the right of the plot. Defaults to TRUE

addfit

A logical value indicating whether the reference measure should be plotted. See Details.

xlim

The horizontal limits of the plot region. If unspecified, the function tries to set the horizontal plot limits to some sensible values. Should not be used by the user.

alim

the actual x axis limits. If unspecified, an educated guess is taken by the function.

ylim

The vertical limits of the plot. If unspecified, the function does what it thinks is best. Should not be used by the user.

at

Position of the x axis tick marks and corresponding labels are placed. If unspecified, the function tries to position them at sensible values.

steps

An integer indicating the number of tick marks on the X axis. Ignored when at is specified. Defaults to 5

digits

integer specyfing the number of decimal places for tick mark labels and annotations. Can also be a vector of two integers. In that case, the first value specifies the number of decimal places for the annotations, the second for the x axis labels.

refline

numerical value indicating where a reference line should be drawn. An NA value will prevent the line from being drawn. See Details.

xlab

title for the x axis. If unspecified, the function tries to figure out the fitting title.

slab

optional vector with names for the displayed genes.

mlab

optional character string giving a label to the intercept estimate. If unspecified, this is created in the function if necessary.

ilab

optional vector or matrix with character strings providing additional information that can be plotted next to the genes.

ilab.xpos

Vector of numerical values specifying the x axis positions of the character vectors given via ilab. This has to be specified when ilab is specified.

ilab.pos

integer from 1 to 4 specifying the alignment of the character vector(s) given via ilab (2 is right aligned, 4 is left aligned). Default is to center the labels.

order

optional character string, character vector or numerical vector specifying how the genes should be ordered.

transf

optional argument specifying the name of a function that should be used to transform the observed effect sizes, summary estimates, fitted values and confidence interval bounds (e.g., transf=exp). Defaults to FALSE, which means that no transformation is used.

atransf

optional argument specifying the name of a function that should be used to transform the x-axis labels and annotations (e.g., transf=exp). Defaults to FALSE, which means that no transformation is used.

targs

optional arguments needed by the function specified via transf or atransf.

rows

optional vector specifying the horizontal position for the plotted results. If unspecified, the layout happens automatically. See Details and Examples for more information.

efac

numerical value specifying the vertical expansion of the arrows, summary estimate symbols and Ci limits. Normally the default of 1 should work just fine.

pch

plotting symbol used for the observed effect sizes. By default, it's a filled square.

psize

optional vector with the point sizes for the observed effects. If set to NULL, the point sizes are drawn proportional to the value of the log of the test statistic. Defaults to 1.

col

character string specifying the color used for the individual estimates.

border

character string specifying the color used for the border of the individual estimates.

cex

optional numerical value for expansion of text and symbols. See also par.

cex.lab

Optional numerical value for expansion of the axis title.

cex.axis

Optional numerical value for expansion of the x axis labels.

refcol

Character string specyfying the color of the reference line. Defaults to red.

predcol

character string specifying the color of the estimated reference value. Ignored if estimate is logor or or.

Details

The function has methods for uwmwRes and uwmwEstimate objects. When called for an uwmwRes object, the requested estimate is first calculated using getEstimate and the result is passed on to the next method.

Note that in either case, it is not possible to use the function on a subset of either type of object. The subsetting functions for uwmwRes and uwmwEstimate objects return matrices, and hence necessary information on the reference value is lost. To plot a subset of your data, use the order argument as shown in the examples.

Adding a reference value to the plot only makes sense when plotting the log(odds), odds or probabilities. If log(OR) or OR are plotted, addfit is set to FALSE.

The default settings plot a reference line at a location depending on the plotted estimate. For log(OR), the line is plotted at refline = 0. For OR, the line is plotted at refline = 1.

Value

NULL invisibly

Warning

Although the internal function is shown here (merely for illustration of the arguments and defaults), the user shouldn't be calling this one directly. The function is not exported.

Note

Thanks to the work of W.Viechtbauer, forestplot provides many possibilities for tweaking and customizing the plots. Many of the arguments work the same as in the function forest.rma (metafor package). You can always check the help file of forest.rma for more illustrations on the different arguments.

This function is currently implemented using an internal function that expects an uwmwEstimate object. In a future version, the internal function will be rewritten to be more generic. This will enable the definition of methods for other classes without need to change the internal function itself.

Author(s)

This code is adapted by Joris Meys from the function forest.rma (metafor package). The original function is written by W. Viechtbauer.

Examples

data(NBmat)
NBtest <- uWMW(NBmat, groups=NBgroups)
sigid <- which(pval(NBtest) < 0.05)
forestplot(NBtest,"logodds",order=sigid)

nameid <- c("hsa-mir-30a-3p","hsa-mir-30a-5p")
forestplot(NBtest,"p",order=nameid,addfit=FALSE,
           refline=NA,main="Comparison 30a")

forestplot(NBtest,"p",order=nameid,addfit=FALSE,
           refline=0.5,main="Comparison 30a",
           alim=c(0,1),xlim=c(-1,2),at=c(0,0.5,1))

Extract logor, or, odds and percentages from a uwmwRes object

Description

With this function you can extract the modelled (log) odds ratio, odds or percentages that represent the chance on differential expression as estimated by the uWMW function. It also allows to extract either the standard error of or the confidence interval around the estimates. See Details for more explanation.

Usage

## S4 method for signature 'uwmwRes'
getEstimate(x, esttype = c("logor", "or", "logodds",
  "odds", "p"), se.fit = (esttype %in% c("logor", "logodds")), ci = TRUE,
  drop = TRUE)

Arguments

x

an object of the clas uwmwRes

esttype

a character string indicating the measure you want to extract. It can take the values logor for the log odds ratio, or for the odds ratios, logodds for the log odds, odds for the odds or p for the percentages.

se.fit

logical value indicating whether the standard errors of the logor or the log odds should be returned as well. Ignored when type has a value different from logor or logodds. Note that you can also use the accessor se to get only the standard errors.

ci

numerical value indicating the confidence interval (0.95 is 95% confidence interval). If set to TRUE, the 95 interval is returned. If set to NULL, no confidence interval is returned.

drop

a logical value. If set to TRUE and neither se nor ci is calculated, the function returns a vector instead of an uwmwEstimate object.

...

passes on arguments to the next method

Details

The function can only calculate standard errors for the log OR and the log odds. In all other cases, se.fit is ignored. The function takes into account a possible ordering in the object (see also sort). So take into account that you get the estimates in the specified order. In case you want this different, either use the function unorder on the object first, or check if any of the uwmw_Accessors can help you out.

The argument se.fit is mainly to be used to save calculation time. Normally there's no need to set it to FALSE.

Value

In general, a uwmwEstimate object with the requested estimate. See uwmwEstimate for details. In case drop=TRUE and neither the standard error nor the confidence interval is calculated, a numeric named vector.

Examples

data(NBmat)
NBtest <- uWMW(NBmat, groups=NBgroups)
getEstimate(NBtest,'logodds')
getEstimate(NBtest,'odds',ci=0.9)

Documentation for the dataset NBdata

Description

The example data used in this package, are a subset of the data provided by Mestdagh et al. (2009). The subset contains quantification cycles of 323 microRNAs in 61 neuroblastoma (NB) tumor samples: 22 MYCN amplified (called MNA) and 39 MYCN single copy samples (called MNSC). The subset was selected so that all microRNAs with a least 85

Details

The data exists in different formats. NBdata gives you a data frame with following variables:

subject:

variable of class "factor", indicating the subject code.

miRNA:

variable of class "factor", indicating the miRNA code.

Cq:

variable of class "numeric", containing the cycle information.

group:

variable of class "factor", indicating the group code.

The data matrix NBmat contains the same data in matrix format, where the rows are the different miRNA's and the columns the different subjects. The vector NBgroups specifies to which group every column of NBmat belongs.

References

Mestdagh, P., P. Van Vlierberghe, A. De Weer, D. Muth, F. Westermann, F. Speleman, and J. Vandesompele (2009) A novel and universal method for microRNA RT-qPCR data normalization. Genome Biology., 10, R64.

De Neve, J. Thas, O. Ottoy, J.P. and Clement L. (2013) An extension of the Wilcoxon-Mann-Whitney test for analyzing RT-qPCR data. Statistical Applications in Genetics and Molecular Biology. 12, 333-346.

Examples

# Look at the data frame
data(NBdata)
str(NBdata)

# Look at the matrix and grouping vector
data(NBmat)
str(NBmat)
str(NBgroups)

Quick forest plot of significantly up- and downregulated features.

Description

This function plots a forest plot, normally used in meta analysis, to visualize the odds ratios (OR) and confidence intervals resulting from a call to uWMW. It is the default plot function for the uwmwRes objects. The results are ordered according to significance, and only the significant results are plotted. This function calls forestplot directly.

Usage

## S4 method for signature 'uwmwRes,ANY'
plot(x, y, ...)

Arguments

x

an uwmwRes object.

y

ignored for uwmwRes objects

...

arguments passed down to forestplot

Value

NULL invisibly

See Also

forestplot

Examples

data(NBmat)
NBtest <- uWMW(NBmat, groups=NBgroups)
plot(NBtest)

Extract info from uwmwRes and uwmwEstimate objects

Description

This help file describes different ways to access the slots and values contained in uwmwRes objects resulting from calls to uWMW, and in uwmwEstimate objects resulting from calls to getEstimate.

Usage

type(x)

## S4 method for signature 'uwmwRes'
type(x)

## S4 method for signature 'uwmwEstimate'
type(x)

## S4 method for signature 'uwmwRes'
housekeeping(x)

## S4 method for signature 'uwmwEstimate'
housekeeping(x)

## S4 method for signature 'uwmwRes'
names(x)

## S4 method for signature 'uwmwEstimate'
names(x)

## S4 method for signature 'uwmwRes'
logor(x, ordered = TRUE)

## S4 method for signature 'uwmwRes'
se(x, ordered = TRUE)

## S4 method for signature 'uwmwEstimate'
se(x)

## S4 method for signature 'uwmwRes'
oddsRatio(x, ordered = TRUE)

## S4 method for signature 'uwmwRes'
zval(x, ordered = TRUE)

## S4 method for signature 'uwmwRes'
pval(x, ordered = TRUE)

## S4 method for signature 'uwmwRes'
coef(object)

## S4 method for signature 'uwmwRes'
vcov(object)

## S4 method for signature 'uwmwEstimate'
ref(x)

## S4 method for signature 'uwmwEstimate'
esttype(x)

## S4 method for signature 'uwmwRes'
getOrder(x)

is.unsorted(x, na.rm = FALSE, strictly = FALSE)

## S4 method for signature 'uwmwRes'
orderedBy(x)

## S4 method for signature 'uwmwEstimate'
orderedBy(x)

## S4 method for signature 'uwmwRes'
groupinfo(x)

## S4 method for signature 'uwmwEstimate'
groupinfo(x)

## S4 method for signature 'uwmwEstimate'
length(x)

## S4 method for signature 'uwmwRes'
length(x)

Arguments

x

a uwmwRes object or a uwmwEstimate object.

ordered

logical value. If set to FALSE, the extracted values are given in the original order, also after a uwmwRes object has been ordered using sort. Defaults to TRUE

object

see x

na.rm

for compatibility with the base function is.unsorted. Ignored for uwmwRes objects.

strictly

for compatibility with the base function is.unsorted. Ignored for uwmwRes objects.

Value

type(x) returns the type of uWMW carried out (i.e. O or H for using overall respectively housekeeping expression as a reference.)

housekeeping(x) returns the content of the housekeeping slot from the object. Or, in case of overall normalization, it returns NULL.

names(x) returns the names of the genes in the object, and in the order defined in the object.

logor(x) returns a numeric vector with the log OR values.

se(x) returns a numeric vector with the standard errors on the logor.

oddsRatio(x) returns a numeric vector with the odds ratios.

zval(x) returns a numerical vector with the Z values contained in the object.

pval(x) returns a numerical vector containing the p values in the object.

orderedBy(x) returns the slot by which the object is ordered (i.e. the value of the slot orderedBy)

groupinfo(x) returns the groupinfo slot, i.e. a character vector of length 2 that indicates in which order the groups are compared by uWMW.

See Also

uwmw_Extract for matrix like extraction of data.

Examples

data(NBmat)
NBtest <- uWMW(NBmat,NBgroups)
coef(NBtest)[1:10]
type(NBtest)

# With a sorted object
NBsort <- sort(NBtest, which="p")
is.unsorted(NBtest)
is.unsorted(NBsort)
orderedBy(NBsort)

# On an Estimate object
NBlogodds <- getEstimate(NBsort,"logodds")
se(NBlogodds)
# and so on...

Sort and order method for uWMWRes objects

Description

This functions provide sorting functionality for uwmwRes objects. It allows to sort the values in the object in order to get the genes with the highest OR, lowest p value, ... The function uses order underneath

Usage

unorder(x, ...)

## S4 method for signature 'uwmwRes'
sort(x, decreasing = FALSE, which = c("or", "p", "se",
  "name", "z"), na.last = TRUE, ...)

## S4 method for signature 'ANY'
unorder(x, ...)

## S4 method for signature 'uwmwRes'
unorder(x, ...)

## S4 method for signature 'uwmwRes'
order(..., na.last = TRUE, decreasing = FALSE,
  method = c("auto", "shell", "radix"))

Arguments

x

a uwmwRes object

...

currently ignored

decreasing

a logical value indicating whether values should be sorted in increasing or decreasing order.

which

a character value indicating on which values should be used to sort on. The possible values are: "or" for sorting on the odds ratio, "p" for sorting on the p value, "se" for sorting on the standard error or "name" for sorting on the gene names.

na.last

a logical value indicating whether NA results should be sorted at the end. See order for more information.

method

Argument of the generic, ignored here. See also order

Details

The function does not change the internal order, but changes the slot id in the object. This slot is used by other functions to give the requested values

Value

sort returns a sorted uwmwRes object.

See Also

The functions is.unsorted, orderedBy and getOrder to check on the ordered state of a uwmwRes object.

order returns the order of the uwmwRes object.

unorder returns a uwmwRes object with the order removed.

Examples

data(NBmat)
NBtest <- uWMW(NBmat, groups=NBgroups)
NBsort <- sort(NBtest,which="name")
NBsort[1:10]

Extract data from uwmwRes and uwmwEstimate objects.

Description

For both uwmwRes and uwmwEstimate objects, you can use the square bracket operators to extract information much like you would do for a matrix.

Usage

## S4 method for signature 'uwmwRes,character'
x[i, j, drop = TRUE]

## S4 method for signature 'uwmwEstimate,character'
x[i, j, drop = TRUE]

## S4 method for signature 'uwmwRes,ANY'
x[i, j, drop = TRUE]

## S4 method for signature 'uwmwEstimate,ANY'
x[i, j, drop = TRUE]

Arguments

x

a uwmwRes object

i

numeric or character vector

j

optional numeric or character vector

drop

logical value. If set to FALSE and the result of the extraction is a single row or column, dimensions are dropped. Defaults to TRUE.

Details

The features can be extracted using the row index, and the estimates as

Value

mostly a matrix, unless drop=TRUE and a single row or column is selected. Then a vector.

Examples

# With an uwmwRes object
data(NBmat)
NBtest <- uWMW(NBmat,NBgroups)
# These two lines are the same
NBtest["hsa-mir-1"]
NBtest["hsa-mir-1", ]
# These two not
str(NBtest["hsa-mir-1",,drop=FALSE])
str(NBtest["hsa-mir-1",])
# These two give the same data, but in a different way:
se(NBtest) # unnamed
NBtest[,"se"] #

# With an uwmwEstimate object
NBodds <- getEstimate(NBtest,"odds")
gnames <- grep("let",names(NBodds),value=TRUE)
NBodds[gnames]
NBodds[gnames,c("ll","ul")]

The unified Wilcoxon-Mann-Whitney test for qPCR data

Description

This function carries out the unified Wilcoxon-Mann-Whitney test for qPCR data. See De Neve et al. (2013) for more details.

Usage

## S4 method for signature 'matrix'
uWMW(x, groups, housekeeping.names = NULL,
  transpose = FALSE, feat.names = NULL)

## S4 method for signature 'qPCRset'
uWMW(x, feat.names = NULL, ...)

## S4 method for signature 'data.frame'
uWMW(x, groups, feat.names, subjects, value, ...)

Arguments

x

An object containing the qPCR measurements. See details.

groups

A vector indicating the groups that need comparing, or a single character telling which variable in the data frame contains the groups. Make sure this vector is as long as the number of replicates in the data set.

housekeeping.names

an (optional) vector with the names of one or more housekeeping features. Make sure those names are spelled exactly as in the object.

transpose

In case a matrix is used, should the matrix be transposed? A matrix needs to be transposed when the columns do not represent the replicates. The function expects the columns to be replicates and the rows to be the different features.

feat.names

An (optional) character vector with the names of the features (typically genes or microRNAs) or a single character giving the name of the feature variable. If not specified, the feature names are derived from the row names of the matrix, or from the feature names of the qPCRset object.

...

For passing arguments between methods and to internal functions.

subjects

An (optional) character string indicating which variable of the data frame contains the subject id's. Ignored if x is not a data frame.

value

An (optional) character string indicating which variable of the data frame contains the values. Ignored if x is not a data frame.

Details

This function carries out the unified Wilcoxon-Mann-Whitney test using either Overall normalization (O) or Housekeeping normalization (H) as reference (see De Neve et al., 2013). If the argument housekeeping.names is specified, housekeeping normalization is considered. Otherwise overall normalization is considered.

The function uWMW can deal with data frames, matrices and qPCRset objects from the package HTqPCR. When using a data frame, you need to specify the arguments groups, feat.names, subjects and value; each one should contain the name of the related variable in the data frame.

When using a matrix, each column is assumed to be a subject and each row a feature. The argument groups should contain as much values as there are columns in the matrix. Note that the method for qPCRset objects does nothing else but extract the data matrix and do the analysis. You still need to specify where the groups are to be found.

Value

An object of the class uwmwRes, containing the results of the unified Wilcoxon-Mann-Whitney test. See the help page of the class uwmwRes for more information.

Author(s)

Wrapper methods are written by Joris Meys. Internal functions are written by Jan De Neve.

References

De Neve, J. Thas, O. Ottoy, J.P. and Clement L. (2013) An extension of the Wilcoxon-Mann-Whitney test for analyzing RT-qPCR data. Statistical Applications in genetics and Molecular Biology. 12, 333-346

See Also

uwmw_Accessors and uwmw_Extract for accessing the results, and volcanoplot and forestplot for plotting them.

Examples

data(NBmat)
NBtest <- uWMW(NBmat, groups=NBgroups)

data(NBdata)
NBtest <- uWMW(x = NBdata, groups = "group", sub="subject",feat="miRNA",val="Cq")
head(NBtest)
as.matrix(NBtest)

The class uwmwEstimate

Description

This class represents an estimate object resulting from a call to getEstimate. It contains all information about the estimate, including standard errors and confidence intervals if requested. For this class a number of methods is foreseen, including the accessors for the slots. The class is sortable and can be indexed, so you can use this for making custom forest plots using the function forestplot.

Details

#' @section Slots:

esttype:

object of class "character", containing the estimate type. This can be logor for log odds ratio, or for odds ratio, odds, logodds for the log odds or p for the probability.

names:

object of class "character", containing the names of the genes for which the estimates are calculated.

est:

object of class "numeric", containing the estimates itself.

se:

object of class "numeric", containing the estimates for the standard error, if applicable.

ll:

object of class "numeric", containing the lower limit of the confidence interval.

ul:

object of class "numeric", containing the upper limit of the confidence interval.

refest:

object of class "numeric", containing the estimate for the reference used in the analysis. Note that this only makes sense for log odds, odds and probabilities.

refse:

object of class "numeric", containing the se estimate for the reference if applicable.

refll:

object of class "numeric", containing the lower limit for the reference if applicable.

reful:

object of class "numeric", containing the upper limit for the reference if applicable.

type:

vector of class "character", containing the type of reference used in the original analysis. This can be either "O" or "H" for Overall respectively Housekeeping Expression as reference.

confint:

vector of class "numeric"

, indicating the limit used for the confidence interval. 0.95 represents the 95% confidence interval.

housekeeping:

object of class "character", containing either NULL or the names of the housekeeping genes used in the H version of uWMW.

groupinfo:

character vector of length 2, indicating the groups. This slot is mainly used to show how the probabilistic indices are calculated.

Note

For this class, show and length methods are defined. length will give you the number of features.

Author(s)

Joris Meys


Class uwmwRes

Description

This class represents the results of the unified Wilcoxon-Mann-Whitney test. It contains all necessary information for the vulcano and forest plots. For this class a number of methods is foreseen, among which accessors for every slot.

Slots

type:

object of class "character", containing the type of analysis (either H or O, see uWMW for more details.)

housekeeping:

object of class "character", containing either NULL or the names of the housekeeping features used in the HME version of uWMW.

names:

object of class "character", containing the names of the features that were used in the test.

logOR:

object of class "numeric", containing the estimated log odds ratios from the uWMW test.

se:

object of class "numeric", containing the standard errors on the estimated log odds ratios.

OR:

object of class "numeric", containing the odds ratios estimated by the uWMW test. This slot is accessed using the function oddsRatio()

z.value:

object of class "numeric", containing the Z values related to the odds ratios estimated by the uWMW test. These z-values relate to the chance that a specific feature is up- or downregulated, and are used as the basis for determining the p values.

p.value:

object of class "numeric", containing the p values related to the odds ratios estimated by the uWMW test. These p-values relate to the chance that a specific feature is up- or downregulated.

coef:

object of class "numeric", containing the estimated coefficient of the PIM model that's used in the uWMW test.

vcov:

matrix of class "numeric", containing the variance-covariance matrix related to the estimated coefficients.

id:

vector of class "numeric", containing the sorting order of the features. This slot is set using the function sort

orderedBy:

character value, indicating whether the object contains an order and if so, based on which slot. Possible values are "none", "p", "z", "or", "se" or "name". Defaults to "none".

groupinfo:

character vector of length 2, indicating the groups. This slot is mainly used to show how the probabilistic indices are calculated.

Note

For this class, show and length methods are defined. length will give you the number of features.

Author(s)

Joris Meys

See Also

uwmw_Accessors


Parameters used for the function volcanoplot

Description

The parameters described can all be used in the different volcanoplot methods.

Arguments

highlight

an integer, indicating how many of the top features should be highlighted. Defaults to 0.

names

an optional character vector giving the names of the genes to be highlighted. If not specified, the features are numbered from most significant to least significant. Default value is NULL.

xlab

see par. Defaults to "Fit"

ylab

see par. Defaults to "Significance"

pch

see par. Defaults to 16

cex

see par. Defaults to 0.35 as in the limma package.

transf.x

a function used to transpose the values on the X axis. Defaults to NULL, unless otherwise specified in the specific methods.

transf.y

a function used to transpose the values on the Y axis. Defaults to NULL, unless otherwise specified in the specific method.

add.ref

a charater value indicating if reference lines for x, y or both axes should be drawn. It takes the values "none", "x", "y" or "both". Default value is "none". If not specified but ref.x or ref.y is, then the reference line is drawn for the X and/or the Y axis.

ref.x

a numerical vector, indicating the value or values at which the reference line(s) should be drawn on the X axis. Defaults to NULL.

ref.y

a numerical value, indicating the value at which the reference line should be drawn on the Y axis. Defaults to NULL unless otherwise specified in the specific methods.

col.x

The color for the reference line on the X axis. The argument is passed to the col argument of lines, so check that help page for possible values. Defaults to "darkgrey"

col.y

see col.x, but for the Y axis. If col.x is specified and col.y is not, then the value of col.x is used for col.y.

lwd.x

The line width for the reference line on the X axis. The argument is passed to the lwd argument of lines, so check that help page for possible values. Defaults to 1.

lwd.y

see lwd.x, but for the Y axis. If lwd.y is not specified and lwd.x is, that value is used for lwd.y as well.

lty.x

The line type for the reference line on the X axis. The argument is passed to the lty argument of lines, so check that help page for possible values. Defaults to 1.

lty.y

see lty.x, but for the Y axis. If lty.y is not specified and lty.x is, that value is used for lty.y as well.

Details

The arguments highlight and names are chosen in such a way that the function can mimick the behaviour of the volcanoplot function in the package limma.

Note

These parameters belong to the internal function, eventually called by the different S4 methods. This internal function is not exported, and should not be called directly.

Examples

# see the help page of volcanoplot

Make a volcano plot of the outcome of a uWMW test

Description

This function creates a volcano plot of the outcome of a uWMW test. In this plot, the p-value is plotted against the odd ratio or the log-odds ratio, depending on what interests you most. It allows to quickly see what proportion of results is significant, and what proportion of significant results has a biologically significant chance of being upregulated.

Usage

## S4 method for signature 'uwmwRes'
volcanoplot(fit, esttype = c("logor", "or", "logodds",
  "odds", "p"), transf.y = function(i) -log10(i), ref.y = -log10(0.05), ...)

## S4 method for signature 'matrix'
volcanoplot(fit, ...)

## S4 method for signature 'numeric'
volcanoplot(fit, ...)

## S4 method for signature 'MArrayLM'
volcanoplot(fit, coef = 1, highlight = 0, ...)

Arguments

fit

a uwmwRes object, a matrix with 2 columns or a numeric vector with either odds ratios or the log of odds ratios.

esttype

The estimate that should be plotted from the uwmwRes object. See also getEstimate.

transf.y

a function used to transpose the values on the Y axis. For uwmwRes objects, defaults to -log10(y). Passed down to internal function.

ref.y

The location on the Y axis for the reference line.

...

arguments passed to the internal function. See volcanopar

coef

for compatibility with limma package, see volcanopar

highlight

for compatibiity with limma package, see volcanopar

Details

The methods described here all use the same internal function to create the plot

Value

invisible NULL

Author(s)

Joris Meys

Examples

data(NBmat)
housekeeping.id <- grep("let",rownames(NBmat),value=TRUE)
NB.Htest <- uWMW(NBmat,NBgroups,housekeeping.id)

volcanoplot(NB.Htest)
volcanoplot(NB.Htest,"p")