Description Usage Arguments Creating objects Extends Slots Methods Author(s) References See Also Examples
Classes to perform rowbyrow paired or unequal variance ttests on microarray or proteomics data.
1 2 3 4 5 6  MultiTtestPaired(data, classes, pairing)
MultiTtestUnequal(data, classes)
## S4 method for signature 'MultiTtestPaired'
summary(object, ...)
## S4 method for signature 'MultiTtestUnequal'
summary(object, ...)

data 
Either a data frame or matrix with numeric values or an

classes 
If 
pairing 
A numerical vector indicating which samples are paired. 
object 
A 
... 
Unused; optional extra parameters for 
Although objects can be created using new
, the better method is
to use the MultiTtestPaired
or MultiTtestUnequal
functions. In the simplest case, you simply pass in a data matrix
and a logical vector assigning classes to the columns (and, in the
case of a paired ttest, a numeric vector describing the pairing), and
the constructor performs rowbyrow twosample ttests and computes
the associated (single test) pvalues. To adjust for multiple
testing, you can pass the pvalues on to the Bum
class.
If you use a factor instead of a logical vector, then the ttest
compares the first level of the factor to everything else. To handle
the case of multiple classes, see the MultiLinearModel
class.
As with other class comparison functions that are part of the OOMPA,
we can also perform statistical tests on
ExpressionSet
objects from
the BioConductor libraries. In this case, we pass in an
ExpressionSet
object along with the name of a factor to use for
splitting the data.
Both classes extend class MultiTtest
, directly. See that
class for descriptions of the inherited methods and slots.
df
:The MultiTtestUnequal
class adds a slot to
record e genebygene degrees of freedom, which can change along
with the variances.
signature(object = MultiTtestPaired)
:
Write out a summary of the object.
signature(object = MultiTtestUnequal)
:
Write out a summary of the object.
Kevin R. Coombes krc@silicovore.com
OOMPA
1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16  showClass("MultiTtestPaired")
showClass("MultiTtestUnequal")
ng < 10000
ns < 50
dat < matrix(rnorm(ng*ns), ncol=ns)
cla < factor(rep(c('A', 'B'), each=25))
res < MultiTtestUnequal(dat, cla)
summary(res)
hist(res, breaks=101)
plot(res, res@p.values)
pairing < rep(1:25, 2)
res < MultiTtestPaired(dat, cla, pairing)
summary(res)
plot(res)
hist(res@p.values, breaks=101)

Loading required package: oompaBase
Class "MultiTtestPaired" [package "ClassComparison"]
Slots:
Name: t.statistics p.values df groups call
Class: numeric numeric numeric character call
Extends: "MultiTtest"
Class "MultiTtestUnequal" [package "ClassComparison"]
Slots:
Name: df t.statistics p.values groups call
Class: numeric numeric numeric character call
Extends: "MultiTtest"
Results of an unequal variance ttest
Rowbyrow twosample ttests with 10000 rows
Positive sign indicates an increase in class: A
Call: MultiTtestUnequal(data = dat, classes = cla)
Tstatistics:
Min. 1st Qu. Median Mean 3rd Qu. Max.
4.081715 0.682000 0.000059 0.012435 0.670699 4.392900
Pvalues:
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.0000633 0.2501481 0.5027176 0.5027184 0.7580854 0.9999789
Results of a paired ttest
Rowbyrow twosample ttests with 10000 rows
Positive sign indicates an increase in class: A
Call: MultiTtestPaired(data = dat, classes = cla, pairing = pairing)
Tstatistics:
Min. 1st Qu. Median Mean 3rd Qu. Max.
4.317574 0.677223 0.000059 0.012730 0.682880 4.421023
Pvalues:
Min. 1st Qu. Median Mean 3rd Qu. Max.
0.0001811 0.2510248 0.5030478 0.5024540 0.7583527 0.9999794
Add the following code to your website.
For more information on customizing the embed code, read Embedding Snippets.