make_plot_data | R Documentation |
makeMatrix()
constructs a matrix of PSI values of the given alternative
splicing events (ASEs).
makeMeanPSI()
constructs a table of "average" PSI values, with samples
grouped by a number of given conditions (e.g. "group A" and "group B") of a
given condition category (e.g. condition "treatment").
See details below.
makeMatrix(
se,
event_list,
sample_list = colnames(se),
method = c("PSI", "logit", "Z-score"),
depth_threshold = 10,
logit_max = 5,
na.percent.max = 0.1
)
makeMeanPSI(
se,
event_list = rownames(se),
condition,
conditionList,
depth_threshold = 10,
logit_max = 10
)
se |
(Required) A NxtSE object generated by makeSE |
event_list |
A character vector containing the names of ASE events
(as given by the |
sample_list |
(default = |
method |
In |
depth_threshold |
(default = 10) Samples with the number of reads supporting either included or excluded isoforms below this values are excluded |
logit_max |
PSI values close to 0 or 1 are rounded up/down
to |
na.percent.max |
(default = 0.1) The maximum proportion of values in
the given dataset that were transformed to |
condition |
The name of the column containing the condition values in
|
conditionList |
A list (or vector) of condition values of which to calculate mean PSIs |
Note that this function takes the geometric mean of PSI, by first converting all values to logit(PSI), taking the average logit(PSI) values of each condition, and then converting back to PSI using inverse logit.
Samples with low splicing coverage (either due to insufficient sequencing
depth or low gene expression) are excluded from calculation of mean PSIs.
The threshold can be set using depth_threshold
. Excluding these samples is
appropriate because the uncertainty of PSI is high when the total included /
excluded count is low. Note that events where all samples in a condition is
excluded will return a value of NaN
.
Using logit-transformed PSI values is appropriate because PSI values are
bound to the (0,1) interval, and are often thought to be beta-distributed.
The link function often used with beta-distributed models is the logit
function, which is defined as logit(x) = function(x) log(x / (1 - x))
,
and is equivalent to stats::qlogis. Its inverse is equivalent to
stats::plogis.
Users wishing to calculate arithmetic means of PSI are advised to use makeMatrix, followed by rowMeans on subsetted sample columns.
For makeMatrix
: A matrix of PSI (or alternate) values, with
columns as samples and rows as ASE events.
For makeMeanPSI
: A 3 column data frame, with the first column containing
event_list
list of ASE events, and the last 2 columns containing the
average PSI values of the nominator and denominator conditions.
makeMatrix()
: constructs a matrix of PSI values of the given
alternative splicing events (ASEs)
makeMeanPSI()
: constructs a table of "average" PSI values
se <- SpliceWiz_example_NxtSE()
colData(se)$treatment <- rep(c("A", "B"), each = 3)
event_list <- rowData(se)$EventName
mat <- makeMatrix(se, event_list[1:10])
diag_values <- makeMeanPSI(se, event_list,
condition = "treatment",
conditionList = list("A", "B")
)
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