Introduction to meta conditions with JACUSA2helper
Michael Piechotta
2023-01-18
Source:vignettes/JACUSA2helper-meta-conditions.Rmd
JACUSA2helper-meta-conditions.RmdSee vignette("JACUSA2helper") for general description of
analysis with JACUSA2helper. For details on JACUSA2, check the JACUSA2
manual.
In the following, the use of meta conditions to combine multiple pairwise comparisons will be shown.
Meta condition
JACUSA2helper supports the analysis of several related JACUSA2 result
files via results <- read_results(files, meta_conds)
where meta_conds is a vector of strings that provides a
descriptive name for each file in the vector of strings
files.
Here, we will use the the Zhou et al. (2018) data set,
where the authors map RNA modification of pseudouridine (\(\Psi\)) by chemically modifying
pseudouridines with carbodiimide (+CMC) and detecting arrest events that
are induced by reverse transcription stops in high-throughput sequencing
under 3 different conditions (HIVRT, SIIIMn, and SIIIMg). All three data
sets are available in JACUSA2helper via data().
Additionally, we have compiled combined data sets
data(Zhou2018_call2) and
data(Zhou2018_rt_arrest) that utilizes meta conditions.
Note, that this data has NO replicates!
data(Zhou2018_rt_arrest)
unique(Zhou2018_rt_arrest$meta_cond)
#> [1] HIVRT SIIIRTMn SIIIRTMg
#> Levels: HIVRT SIIIRTMg SIIIRTMnGroup By Site (and other)
When manipulating a multi results object created by
read_results(), it is crucial to distinguish the following
files in an analysis pipeline:
results %>% ... other functions()results %>% dplyr:group_by(results, meta_cond) %>% ... other functions()
The first statement will apply any subsequent functions to ALL sites regardless of the meta condition while the last statement will apply to sites of EACH meta condition!
Number of sites
The following statement will determine the number of covered sites per contig and meta condition:
This statement will determine the number of covered sites per contig regardless of the meta condition:
Plot
First, we add a description data_desc of the conditions
to the result object. The data sets of Zhou2018 have been
layout out in such a way that condition 1 and 2 correspond to
carbodiimide (+CMC) treatment and control (-CMC), respectively.
Next, we define a ggplot2 object that allows to merge legend for
different scales. Check combine
legends for details. In brief, we use colour to
represent cond(ition) and linetype to represent repl(icate)
an relate their possible combinations to descriptive
labels.