fragment_inty: =========================================================================...

View source: R/fragment_inty.r View source: R/.ipynb_checkpoints/fragment_inty-checkpoint.r

fragment_intyR Documentation

========================================================================= fragment_inty

fragment_inty performs the intensity fragmentation

Description

fragment_inty makes intensity_fragments based on HL_fragments and assigns all gathered information to the SummarizedExperiment object.

Usage

fragment_inty(inp, cores = 1, pen, pen_out)

Arguments

inp

SummarizedExperiment: the input data frame with correct format.

cores

cores: integer: the number of assigned cores for the task.

pen

numeric: an internal parameter for the dynamic programming. Higher values result in fewer fragments. Default is the auto generated value.

pen_out

numeric: an internal parameter for the dynamic programming. Higher values result in fewer allowed outliers. Default is the auto generated value.

Details

The columns "intensity_fragment" and "intensity_mean_fragment" are added.

fragment_inty makes intensity_fragments and assigns the mean of each fragment.

The function used is:

.score_fun_ave.

The input is the the SummarizedExperiment object.

pen is the penalty for new fragments in the dynamic programming, pen_out is the outlier penalty.

Value

The SummarizedExperiment object:

ID:

The bin/probe specific ID

position:

The bin/probe specific position

intensity:

The relative intensity at time point 0

probe_TI:

An internal value to determine which fitting model is applied

flag:

Information on which fitting model is applied

position_segment:

The position based segment

delay:

The delay value of the bin/probe

half_life:

The half-life of the bin/probe

TI_termination_factor:

String, the factor of TI fragment

delay_fragment:

The delay fragment the bin belongs to

velocity_fragment:

The velocity value of the respective delay fragment

intercept:

The vintercept of fit through the respective delay fragment

slope:

The slope of the fit through the respective delay fragment

HL_fragment:

The half-life fragment the bin belongs to

HL_mean_fragment:

The mean half-life value of the respective half-life fragment

intensity_fragment:

The intensity fragment the bin belongs to

intensity_mean_fragment:

The mean intensity value of the respective intensity fragment

Examples

data(fragmentation_minimal)
fragment_inty(inp = fragmentation_minimal, cores = 2, pen = 2, pen_out = 1)


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