Description Usage Arguments Value Author(s) References See Also
Fits a linear mixed model to qpcr data, allowing for several genes, two-factorial block and split-plot designs. Delta-Ct and DeltaDelta-Ct values are calculated by multiple contrasts.
1 2 3 |
data |
A data.frame object. |
response |
Name of a column in data, denoting a numeric response vector, usually estimated Ct values. |
gene |
Name of a column in data, denoting a factor coding for different genes. |
control_gene |
Name of a single control gene in the vector of gene names. |
fixed1 |
Name of a column in data, denoting a factor coding for several treatment groups |
fixed2 |
Name of a column in data, denoting a second factor coding for several treatment groups, default is NULL |
rep_id |
Name of a column in data, denoting a factor which identifies a biological replication or block. |
block |
Logical; are the rep_ids denoting a block variable? default is FALSE. |
splitplot |
Logical; Is the experiment designed as a split-plot with fixed1 as mainplots and fixed2 as subplot? default is FALSE. |
contrasts |
Logical; If TRUE: Tests for general linear hypotheses are performed. |
interaction |
Logical; If TRUE: Tests for interaction between fixed1 and fixed2 are performed if contrasts==TRUE. |
adjusted |
Logical; Should multiplicity adjusted p-values be reported? default is FALSE. |
df |
Providing degrees of freedom as a numeric value, an input of NULL corresponds to the assumption of a Normal- instead of a t-distribution. |
An object of class qpcrmacro.
Daniel Gerhard <gerhard@biostat.uni-hannover.de>
Steibel, JP, Poletto, R, Coussens, PM, Rosa, GJM (2009): A powerful and flexible linear mixed model framework for the analysis of relative quantification RT-PCR data. Genomics 94:146–152.
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