CoRecMotif-class: CoRecMotif class
In Siggers-Lab/hTF_array: Process and Visualize CoRec Data

CoRecMotif-class

R Documentation

CoRecMotif class

Description

A container for motifs generated by a CoRec experiment.

Usage

## S4 method for signature 'CoRecMotif'
as.data.frame(x)

## S4 method for signature 'CoRecMotif'
show(object)

Arguments

x, object

CoRecMotif. The motif to manipulate.

Slots

probe_set: character(1). The probe set name.
pbm_condition: character(1). The PBM condition (e.g., cell type, treatment, and factor profiled).
zscore_motif: matrix(numeric). The z-score motif. See make_zscore_motif() for a description of the expected format.
array_id: character(1). The name of the array/experiment the z-score motif is from.
motif_strength: numeric(1). Calculated automatically. The motif strength is the 93rd percentile of the z-scores in the z-score motif (or approximately the median of the top 15% of z-scores).
rolling_ic: numeric(1). Calculated automatically. The rolling IC is the maximum value obtained when taking a moving average of the information content of the motif over a sliding window of length 5.
seed_sequence: character(1). The sequence of the seed probe.
beta: numeric(1). Calculated automatically. Beta is defined as 4 - (0.5 * z), where z is the z-score of the seed probe of this probe set. If beta falls outside the range of 1 to 4 (inclusive), it is set to the nearest endpoint. It is used to convert the z-score motif to a PPM.
motif: universalmotif. Calculated automatically. To convert the z-score motif into a PPM, each z-score is first multiplied by beta, and then the product is exponentiated. Each column (or position in the motif) is then normalized to sum to 1.
match_motif: universalmotif. The best match reference motif.
match_pvalue: numeric(1). The adjusted p-value of the best match to a reference motif.
match_cluster: character(1). The cluster of the best match reference motif.