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In version 2.1.3, optional custom model formula can be supplied
by user to ANOVA_DDCt() and ANOVA_DCt()
functions via model argument. If provided, this overrides
the default formula (single- or multi-factorial CRD or RCBD design based
on the availability of block and the number of factors). The formula
uses wDCt as the response variable. For mixed models,
random effects can be supplied (e.g.,
wDCt ~ Treatment * (1| id)).
Handling missing Ct values for target genes using the
set_missing_target_Ct_to_40 function. If TRUE,
missing target gene Ct values become 40; if FALSE
(default), they become NA. missing Ct values of reference genes are
always converted to NA.
The ANOVA_DDCt() and ANOVA_DCt()
functions detect singular fits when a user-defined mixed model (lmer) is
used, and genes that have singular fits after the analysis will be
reported.
Because, currently a model (including repeated measure and ancova
models) can be supplied to ANOVA_DDCt() by user,
REPEATED_DDCt() and ANCOVA_DDCt()functions
were removed. Refer to the vignette for a sample of most common models
and description
For CRD, RCBD, and factorial experiments under CRD or RCBD designs no model is required as one of these models is appropriately selected based on the input arguments.
The non-parametric WILCOX_DDCt() function was added
to analyze the gene expression (ddCt method) using wilcox.test.
ANCOVA analysis which already was performed via the
analysisType = "ancova" argument of the
ANOVA_DDCt() function, now is performed using the
ANCOVA_DDCt() new function. The analysisType
argument was removed.
A function named compute_wDCt() was added which
cleans the data and computes weighted delta Ct (wDCt) values. Handling
missing data by this function has been described in the function
details.
Two arguments of the REPEATED_DDCt() function were
updated in order to be similar to those of the ANOVA_DDCt()
function: The repeatedFactor and
calibratorLevel arguments were changed to
mainFactor.column and mainFactor.level.order,
respectively.
The font size and legend position controls were added to the
efficiency() function.
It is now possible to return the lm formula that is used for
variance analysis in ANOVA_DDCt(), and
REPEATED_DDCt() functions using
object$perGene$gene_name$lm_formula command.
The rtpcr package now accepts any number of references and any number of target genes in a single analysis. The package computes the geometric mean of reference genes considering efficiency values.
Missing data can be denoted by NA in the input data frame. Values such as “0” and “undetermined” (for any E or Ct) are automatically converted to NA before being passed to downstream analyses. For target genes, NA values for E or Ct measurements result in NA for the corresponding ΔCt for that replicate, which is then propagated through downstream statistical analyses. When more than one reference gene is used, NA values in either the E or Ct field for any reference gene cause that reference gene to be skipped, and the remaining reference genes are geometrically averaged.
The long_to_wide() function was added to convert a
4-column qPCR data with long format to wide.
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.