Robust Tests for Differential Dispersion and Differential Expression in RNA-Sequencing Data
Main function. For most users, this function is all what they need for...
Give a rough estimate of the proportion of outliers in the data based ...
Calculates the estimate and standard error of beta and phi. It takes a...
Calls the robnb function to estimate the coefficients, and then constr...
Implements the algorithm described in Jun Li and Alicia T. Lamere, "DiPhiSeq: Robust comparison of expression levels on RNA-Seq data with large sample sizes" (Unpublished). Detects not only genes that show different average expressions ("differential expression", DE), but also genes that show different diversities of expressions in different groups ("differentially dispersed", DD). DD genes can be important clinical markers. 'DiPhiSeq' uses a redescending penalty on the quasi-likelihood function, and thus has superior robustness against outliers and other noise. Updates from version 0.1.0: (1) Added the option of using adaptive initial value for phi. (2) Added a function for estimating the proportion of outliers in the data. (3) Modified the input parameter names for clarity, and modified the output format for the main function.