filterT {ISoLDE} | R Documentation

## FILTERING GENES BEFORE STATISTICAL ANALYSIS

### Description

Filter lowly expressed genes (or transcripts) according to a data driven threshold, before any statistical analysis. This step is not mandatory but strongly recommended.

### Usage

    filterT(rawASRcounts, normASRcounts, target, tol_filter = 0,
    bias)

### Arguments

`rawASRcounts` | the `data.frame` containing raw counts (obtained with the `readRawInput` function or any data.frame following `rawASRcounts` format specifications). Raw count `data.frame` is required when filtering on raw or on normalized data when the normalized data do not contain 0 counts. (For simplicity purpose, we call '0 count' any value of zero in a count file).
`normASRcounts` | the `data.frame` containing normalized counts (obtained with the `readNormInput` function or any data.frame following `normASRcounts` format specifications). We strongly recommend to filter on normalized ASR counts.
`target` | the `data.frame` containing the target meta data (obtained with the `readTarget` function or any data.frame following `target` format specifications).
`tol_filter` | a value between 0 and 100 allowing to introduce tolerance rate into filtering step: if tol_filter = 25 all genes having less than 25% of their counts from at least one parental (or strain) origin below the threshold are selected (the default value 0 means all raw counts from at least one parental (or strain) origin must be above threshold, 100 means that no filtering is applied).
`bias` | The kind of allele expression bias you want to study. It must be one of “parental” or “strain”.

### Details

Filtering in statistical analysis is recommended to avoid considering genes (or transcript) without enough information, and thus to avoid a too strong effect of multiple test correction.

The aim of our filtering method is to eliminate from analysis not enough quantified genes, that is genes having mostly counts of 0 or near 0 for each replicate in at least one condition (parent, strain). In this purpose, the `filterT` function searches for the distribution of counts of a gene in a condition when most of read counts are 0 for this condition. This distribution allows to define a threshold. Hence, genes having less counts than this threshold are eliminated.

The filtering step is not mandatory but strongly recommended.

### Value

A list of two `data.frame`:

``filteredASRcounts`` | This `data.frame` contains ASR counts that have successfully passed the filtering step.
``removedASRcounts`` | This `data.frame` contains ASR counts that have been removed by the filtering step.

Each line represents a feature (e.g. a gene, transcript). Each column represents the number of allele-specific sens reads from either the paternal or maternal parent for a given biological replicate, so that you expect to have two columns per biological replicate.

### Note

`filterT` output on normalized data is the typical input for `isolde_test`.

### Note

A minimal filtering step will always be performed while applying the `isolde_test` function. It consists of eliminating all genes not satisfying these two conditions:
- At least one of the two medians (of paternal or maternal ASR counts) is different from 0;
- There is at least one ASR count (different from 0) in each cross.

### Author(s)

Marine Rohmer marine.rohmer@mgx.cnrs.fr,
Christelle Reynès christelle.reynes@igf.cnrs.fr

### References

Reynès, C. et al. (2016): ISoLDE: a new method for identification of allelic imbalance. Submitted

### Examples

    # Loading all required data.frames
    data(rawASRcounts)
    data(normASRcounts)
    data(target)

    # Filtering genes from the ASR count data.frame in parental bias study
    res_filterT <- filterT(rawASRcounts = rawASRcounts,
                           normASRcounts = normASRcounts,
                           target = target, bias="parental")
    filteredASRcounts <- res_filterT$filteredASRcounts
    removedASRcounts <- res_filterT$removedASRcounts

[Package ISoLDE version 1.8.0 Index]