apply_t_test: =========================================================================...

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

========================================================================= apply_t_test

apply_t_test uses the statistical t_test to check if the fold-change of half -life (HL) fragments and the fold-change intensity fragments respectively are significant.

Description

apply_t_test compares the mean of two neighboring fragments within the same TU to check if the fold-change is significant.Fragments with distance above threshold are not subjected to t-test.Dataframes with less than 3 rows are excluded.

Usage

apply_t_test(inp, threshold = 300)

Arguments

inp	SummarizedExperiment: the input data frame with correct format.
threshold	integer: threshold.

Details

The functions used are:

1. fragment_function: checks number of fragments inside TU, less than 2 are excluded otherwise they are gathered for analysis.

2. t_test_function: excludes dataframes with less than 3 rows, makes fold-change and apply t-test, assign fragments names and ratio, add columns with the corresponding p_values.

Value

the SummarizedExperiment with the columns regarding statistics:

ID:

The bin/probe specific ID.

position:

The bin/probe specific position.

strand:

The bin/probe specific strand.

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.

TU:

The overarching transcription unit.

TI_termination_fragment:

The TI fragment the bin belongs to.

TI_mean_termination_factor:

The mean termination factor of the respective TI fragment.

seg_ID:

The combined ID of the fragment.

pausing_site:

presence of pausing site indicated by +/-.

iTSS_I:

presence of iTSS_I indicated by +/-.

ps_ts_fragment:

The fragments involved in pausing site or iTSS_I.

event_duration:

Integer, the duration between two delay fragments.

event_ps_itss_p_value_Ttest:

p_value of pausing site or iTSS_I.

p_value_slope:

Integer, the p_value added to the inp.

delay_frg_slope:

Integer, the slope value of the fit through the respective delay fragment.

velocity_ratio:

Integer, the ratio value of velocity from 2 delay fragments.

event_position:

Integer, position of the event added to the input.

FC_HL:

Integer, the fold change value of 2 HL fragments.

FC_fragment_HL:

String, the fragments corresponding to HL fold change.

p_value_HL:

Integer, the p_value added to the input of 2 HL fragments.

FC_intensity:

Integer, the fold change value of 2 intensity fragments.

FC_fragment_intensity:

String, the fragments corresponding to intensity fold change.

p_value_intensity:

Integer, the p_value added to the input of 2 intensity fragments.

Examples

data(stats_minimal)
apply_t_test(inp = stats_minimal, threshold = 300)

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