pA_logit_pairwise: pA_logit_pairwise

In goodarzilab/APAlog: Analysis of alternative poly A site usage

pA_logit_pairwise

Description

Function to compare the usage of all pairs of poly sites of a transcript

Usage

pA_logit_pairwise(data, model, design = NULL, sample_ID = NULL)

Arguments

data	Dataset containing poly A (pA) site read counts. This dataset must have a long shape, meaning that there should be only one column containing read counts (and it MUST be named "count"). The first four columns must be called "transcript", "pA.site", "sample" and "count". Thus, each row in data contains the read count for one pA - transcript - sample combination. Other sample attributes beyond sample ID may be recorded in additional variables in this dataset, or provided separately through a design matrix and a key variable (e.g. sample ID) connecting the data and design matrices.
model	Regression model describing the dependence of pA site usage on sample attribute(s).
design	(optional) Design matrix. A matrix describing sample attributes which can be used as predictors in the regression model.
sample_ID	(optional) A key variable connecting the counts dataset (data) and the design matrix.

Value

Log ratios (called "Estimate", logistic regression coefficients) and p-values describing the effect of predictor(s) specified in the model on the usage ratio of pairs of pA sites per trancript. Standard error and z score of estimates are also given.

Examples

fit2_pA <- pA_logit_pairwise(pA.toy2, pA.site~cell_line, pA_design, "sample")

goodarzilab/APAlog documentation built on March 25, 2022, 3:40 p.m.