Description Usage Arguments Value Author(s) References Examples
Performs a DIDS analysis on an ExpressionSet to identify genes that are differentially expressed in (a subset of) the samples the set.
1 | didsScore(eset, modF = 2, modType = "tanh", alt = "two.sided")
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eset |
ExpressionSet object on which the analysis should be performed. The phenoData of the object should contain a 'condition' column that marks each sample as being either 'sensitive' or 'resistant'. |
modF |
Scoring function parameter. Corresponds to the exponent if the quadratic scoring function is used (x^modF) or a scaling factor if the tangent method is used (tanh((x-1)*(1+modF))+1). |
modType |
Type of scoring function used. Options are 'tanh' and 'quad'. The tangent-based method (tanh) weighs small excess expression values (< 1) slightly lower than a linear function, differences between one and two slightly more than the linear case and all differences larger than two are capped at two. It is our experience that this scoring function detects most aberrant patterns. The quadratic scoring function (quad) penalizes small differences (< 1), but exaggerates differences larger than one. This scoring function is suited to detect patterns of infrequent aberrant samples that show a large difference compared to the control group. |
alt |
Specifies whether a one-sided or two-sided test should be performed (i.e. 'greater', 'less' or 'two.sided'). A two-sided test will perform 'less' and 'greater' separately and return the highest score between the two resulting scores for each feature/gene. |
Returns a dataframe with a score and p-value for each gene that reflect how likely the corresponding gene is actually differentially expressed.
Julian de Ruiter wrote this wrapper function of the original DIDS code. DIDS itself was written by Jorma de Ronde.
Identifying subgroup markers in heterogeneous populations. (J de Ronde, et al. 2013.)
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