qPCR

The data set contains 4 classifiers (blocks), i.e.
 bias, linearity, precision and resolution, for 11
 different qPCR analysis methods. The null hypothesis
 is that there is no preferred ranking of the method results
 per gene for the performance parameters analyzed.
 The rank scores were obtained by averaging results
 across a large set of 69 genes in a biomarker data file.

datasets

For one-way layout experiments the one-way ANOVA can
be performed as an omnibus test. All-pairs multiple comparisons
tests (Tukey-Kramer test, Scheffe test, LSD-test)
and many-to-one tests (Dunnett test) for normally distributed
residuals and equal within variance are available. Furthermore,
all-pairs tests (Games-Howell test, Tamhane's T2 test,
Dunnett T3 test, Ury-Wiggins-Hochberg test) and many-to-one
(Tamhane-Dunnett Test) for normally distributed residuals
and heterogeneous variances are provided. Van der Waerden's normal
scores test for omnibus, all-pairs and many-to-one tests is
provided for non-normally distributed residuals and homogeneous
variances. The Kruskal-Wallis, BWS and Anderson-Darling
omnibus test and all-pairs tests
(Nemenyi test, Dunn test, Conover test, Dwass-Steele-Critchlow-
Fligner test) as well as many-to-one (Nemenyi test, Dunn test,
U-test) are given for the analysis of variance by ranks.
Non-parametric trend tests (Jonckheere test, Cuzick test,
Johnson-Mehrotra test, Spearman test) are included.
In addition, a Friedman-test for one-way ANOVA with repeated
measures on ranks (CRBD) and Skillings-Mack test for unbalanced
CRBD is provided with consequent all-pairs tests (Nemenyi test,
Siegel test, Miller test, Conover test, Exact test)
and many-to-one tests (Nemenyi test, Demsar test, Exact test).
A trend can be tested with Pages's test. Durbin's test
for a two-way balanced incomplete block design (BIBD) is given
in this package as well as Gore's test for CRBD with multiple
observations per cell is given.  Outlier tests, Mandel's k- and
h statistic as well as functions for Type I error and Power
analysis as well as generic summary, print and plot methods
are provided.

Thorsten Pohlert

PMCMRplus

Calculate Pairwise Multiple Comparisons of Mean Rank Sums
Extended

qPCR function

A data frame with 4 observations on the following 11 variables.<dl class="dl-horizontal">
 <dt>Cy0</dt><dd>a numeric vector</dd>
 <dt>LinRegPCR</dt><dd>a numeric vector</dd>
 <dt>Standard_Cq</dt><dd>a numeric vector</dd>
 <dt>PCR_Miner</dt><dd>a numeric vector</dd>
 <dt>MAK2</dt><dd>a numeric vector</dd>
 <dt>LRE_E100</dt><dd>a numeric vector</dd>
 <dt>5PSM</dt><dd>a numeric vector</dd>
 <dt>DART</dt><dd>a numeric vector</dd>
 <dt>FPLM</dt><dd>a numeric vector</dd>
 <dt>LRE_Emax</dt><dd>a numeric vector</dd>
 <dt>FPK_PCR</dt><dd>a numeric vector</dd>
 </dl>

Format

qPCR Curve Analysis Methods — qPCR

A data frame with 4 observations on the following 11 variables.<dl class='dl-horizontal'>
 <dt>Cy0</dt><dd>a numeric vector</dd>
 <dt>LinRegPCR</dt><dd>a numeric vector</dd>
 <dt>Standard_Cq</dt><dd>a numeric vector</dd>
 <dt>PCR_Miner</dt><dd>a numeric vector</dd>
 <dt>MAK2</dt><dd>a numeric vector</dd>
 <dt>LRE_E100</dt><dd>a numeric vector</dd>
 <dt>5PSM</dt><dd>a numeric vector</dd>
 <dt>DART</dt><dd>a numeric vector</dd>
 <dt>FPLM</dt><dd>a numeric vector</dd>
 <dt>LRE_Emax</dt><dd>a numeric vector</dd>
 <dt>FPK_PCR</dt><dd>a numeric vector</dd>
 </dl>

qPCR: qPCR Curve Analysis Methods

Description

Arguments

Format

References