NIMEB {MEB} | R Documentation

## Detect differential expression genes for RNA-seq data

### Description

Use a normalization-invariant minimum enclosing ball (NIMEB) method to discriminate differential expression (DE) genes in the same or different species.

### Usage

    NIMEB(countsTable, train_id, gamma, nu = 0.01, reject_rate = 0.1,
    ds = FALSE)

### Arguments

`countsTable` | Matrix or data.frame of short read counts for each genes in the same or different species.
`train_id` | A vector shows the position of housekeeping genes or conserved genes in countsTable.
`gamma` | A parameter needed for all kernels except linear.
`nu` | parameter needed for one-classification.
`reject_rate` | A value used in controling the scale of ball, default is 0.01.
`ds` | A value to show the data is for the same species or different species. If ds is FALSE, the data is the same species, else the data is the different species.

### Value

list(.) A list of results, "model" represents the model of NIMEB, which could be used to discriminate a new gene, "gamma" represents the selected gamma parameters in model NIMEB, "train_error" represents the corresponding train_error when the value of gamma changed.

### Examples

    ## Simulation data for the same species.
    library(SummarizedExperiment)
    data(sim_data_sp)
    gamma <- seq(1e-06,5e-05,1e-06)
    sim_model_sp <- NIMEB(countsTable = assay(sim_data_sp), train_id=1:1000,
    gamma, nu = 0.01, reject_rate = 0.05, ds = FALSE)

    ## Real data for the same species.
    data(real_data_sp)
    gamma <- seq(1e-06,5e-05,1e-06)
    real_model_sp <- NIMEB(countsTable = assay(real_data_sp), train_id=1:530,
    gamma, nu = 0.01, reject_rate = 0.1, ds = FALSE)

    ## Simulation data for the different species.
    data(sim_data_dsp)
    gamma <- seq(1e-07,2e-05,1e-06)
    sim_model_dsp <- NIMEB(countsTable = assay(sim_data_dsp), train_id=1:1000,
    gamma, nu = 0.01, reject_rate = 0.1, ds = TRUE)

    ## Real data for the different species.
    data(real_data_dsp)
    gamma <- seq(5e-08,5e-07,1e-08)
    real_model_dsp <- NIMEB(countsTable = assay(real_data_dsp), train_id=1:143,
    gamma, nu = 0.01, reject_rate = 0.1, ds = TRUE)

[Package MEB version 1.6.0 Index]