make_df: =========================================================================...

In CyanolabFreiburg/rifi: 'rifi' analyses data from rifampicin time series created by microarray or RNAseq

========================================================================= make_df

make_df adds important columns to the SummarizedExperiment object

Description

'make_df' adds to the SummarizedExperiment object with the columns: "intensity", "probe_TI" and "flag".

Usage

make_df(inp, cores = 1, bg = 0, rm_FLT = TRUE)

Arguments

inp	SummarizedExperiment: the (checked) input.
cores	integer: the number of assigned cores for the task.
bg	numeric: threshold over which the last timepoint has to be fitted with the above background mode.
rm_FLT	logical: remove IDs where all replicates are marked as filtered. Default is FALSE.

Details

The replicates are collapsed into their respective means.

"intensity" is the mean intensity from time point 0.

"probe_TI" is a value needed for the distribution for the different fitting models.

"flag" contains information or the distribution for the different fitting models.

Probes that don't reach the background level expression are flagged as "ABG" ("above background"). This is only needed for microarray data and is controlled by the bg parameter. The default for bg = 0, resulting in all probes to be above background (0 is advised for RNAseq data).

Probes where all replicates were filtered in the optional filtration step can be fully removed by rm_FLT = TRUE! If you wish to keep all information in the assay set to FALSE!

Value

the SummarizedExperiment object: with intensity, probe_TI and flag added to the rowRanges.

Examples

data(preprocess_minimal)
make_df(inp = preprocess_minimal, cores = 2, bg = 0, rm_FLT = TRUE)

CyanolabFreiburg/rifi documentation built on May 7, 2023, 7:53 p.m.