newTranslatomeDataset: newTranslatomeDatasetHelpfile
In tRanslatome: Comparison between multiple levels of gene expression

Description Usage Arguments Details Value Author(s) See Also Examples

This function takes as input a normalized data matrix coming from an high-throughput experiment, along with vectors of column names (or numeric vectors of columns) defining the samples for each of the conditions. It takes as an input a character label specifying the data type(array, ngs) and returns an object of the class TranslatomeDataset, which stores the matrix and the samples definitions and allow to call the computeDEGs function on it to compute differentially expressed genes in the various conditions.

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newTranslatomeDataset(expr.matrix, cond.a, cond.b, cond.c, cond.d,
    data.type="array", label.level=c("1st level","2nd level"),
    label.condition=c("control","treated"))

`expr.matrix`	a matrix that contains the normalized signal intensity data, each row representing a gene and each column representing a sample. Row names should correspond to gene names, column names should correspond to sample names,
`cond.a`	a character vector of column names (or a numeric vector of columns) belonging to expr.matrix. These columns contain the signal intensity data coming from the samples of the first level of the control condition (in our example: total RNA, undifferentiated cells),
`cond.b`	a character vector of column names (or a numeric vector of columns) belonging to expr.matrix. These columns contain the signal intensity data coming from the samples of the first level of the treatment condition(in our example: total RNA, differentiated cells),
`cond.c`	a character vector of column names (or a numeric vector of columns) belonging to expr.matrix. These columns contain the signal intensity data coming from the samples of the second level of the control condition (in our example: polysomal RNA, undifferentiated cells),
`cond.d`	a character vector of column names (or a numeric vector of columns) belonging to expr.matrix. These columns contain the signal intensity data coming from the samples of the second level of the treatment group (in our example: polysomal RNA, differentiated cells),
`data.type`	a character specifying the type of data represented by `expr.matrix`. By default it is set to `array`, the other accepted value is `ngs`,
`label.level`	a character vector specifying the names given to the two levels. By default the vector is set to `c("1st level","2nd level")`, but the user can specify other names: in our example the two levels are named "transcriptome" and "translatome",
`label.condition`	a character vector specifying the names given to the two conditions. By default, the vector is set to `c("control","treated")`, but the user can specify other names: in our example the two levels are named "undifferentiated" and "differentiated",

Signals contained in expr.matrix should be previously normalized with standard methods (quantile, percentile shift, ... ) when data is coming from microarrays or in the appropriate cases when it is coming from sequencing experiments.

An object of class TranslatomeDataset

Toma Tebaldi, Erik Dassi, Galena Kostoska

TranslatomeDataset computeDEGs DEGs Scatterplot Histogram CVplot MAplot SDplot

data(tRanslatomeSampleData)
translatome.analysis <-
    newTranslatomeDataset(expressionMatrix,
        c("tot.undiff.a","tot.undiff.b","tot.undiff.c"),
        c("tot.diff.a","tot.diff.b","tot.diff.c"),
        c("pol.undiff.a","pol.undiff.b","pol.undiff.c"),
        c("pol.diff.a","pol.diff.b","pol.diff.c"),
        data.type="array", label.level=c("transcriptome","translatome"),
        label.condition=c("undifferentiated","differentiated"))