optimize.sd_selection {BioTIP} | R Documentation

## optimization of sd selection

### Description

The `optimize.sd_selection` filters a multi-state dataset based on a cutoff value for standard deviation per state and optimizes. By default, a cutoff value of 0.01 is used. Suggested if each state contains more than 10 samples.

### Usage

    optimize.sd_selection(df, samplesL, B = 100, percent = 0.8,
      times = 0.8, cutoff = 0.01, method = c("other", "reference",
      "previous", "itself", "longitudinal reference"), control_df = NULL,
      control_samplesL = NULL)

### Arguments

`df` | A dataframe of numerics. The rows and columns represent unique transcript IDs (geneID) and sample names, respectively.
`samplesL` | A list of n vectors, where n equals to the number of states. Each vector gives the sample names in a state. Note that the vectors (sample names) has to be among the column names of the R object 'df'.
`B` | An integer indicating number of times to run this optimization, default 1000.
`percent` | A numeric value indicating the percentage of samples will be selected in each round of simulation.
`times` | A numeric value indicating the percentage of `B` times a transcript need to be selected in order to be considered a stable signature.
`cutoff` | A positive numeric value. Default is 0.01. If < 1, automatically goes to select top x# transcripts using the a selecting method (which is either the `reference`, `other` or `previous` stage), e.g. by default it will select top 1% of the transcripts.
`method` | Selection of methods from `reference`, `other`, `previous`, default uses `other`. Partial match enabled. `itself`, or `longitudinal reference`. Some specific requirements for each option: `reference`, the reference has to be the first. `previous`, make sure sampleL is in the right order from benign to malign. `itself`, make sure the cutoff is smaller than 1. `longitudinal reference` make sure control_df and control_samplesL are not NULL. The row numbers of control_df is the same as df and all trancript in df is also in control_df.
`control_df` | A count matrix with unique loci as row names and samples names of control samples as column names, only used for method `longitudinal reference`
`control_samplesL` | A list of characters with stages as names of control samples, required for method 'longitudinal reference'

### Value

A list of dataframe of filtered transcripts with the highest standard deviation are selected from `df` based on a cutoff value assigned. The resulting dataframe represents a subset of the raw input `df`.

### Author(s)

Zhezhen Wang zhezhen@uchicago.edu

### See Also

`sd_selection`

### Examples

    counts = matrix(sample(1:100,30),2,30)
    colnames(counts) = 1:30
    row.names(counts) = paste0('loci',1:2)
    cli = cbind(1:30,rep(c('state1','state2','state3'),each = 10))
    colnames(cli) = c('samples','group')
    samplesL <- split(cli[,1],f = cli[,'group'])
    test_sd_selection <- optimize.sd_selection(counts, samplesL, B = 3, cutoff =0.01)

[Package BioTIP version 1.0.0 Index]