fitSSTimeSeries {metagenomeSeq} | R Documentation |
Calculate time intervals of interest using SS-Anova fitted models. Fitting is performed uses Smoothing Spline ANOVA (SS-Anova) to find interesting intervals of time. Given observations at different time points for two groups, fitSSTimeSeries calculates a function that models the difference in abundance between two groups across all time. Using permutations we estimate a null distribution of areas for the time intervals of interest and report significant intervals of time. Use of the function for analyses should cite: "Finding regions of interest in high throughput genomics data using smoothing splines" Talukder H, Paulson JN, Bravo HC. (In preparation)
fitSSTimeSeries( obj, formula, feature, class, time, id, lvl = NULL, include = c("class", "time:class"), C = 0, B = 1000, norm = TRUE, log = TRUE, sl = 1000, featureOrder = NULL, ... )
obj |
metagenomeSeq MRexperiment-class object. |
formula |
Formula for ssanova. Of the form: abundance ~ ... where ... includes any pData slot value. |
feature |
Name or row of feature of interest. |
class |
Name of column in phenoData of MRexperiment-class object for class memberhip. |
time |
Name of column in phenoData of MRexperiment-class object for relative time. |
id |
Name of column in phenoData of MRexperiment-class object for sample id. |
lvl |
Vector or name of column in featureData of MRexperiment-class object for aggregating counts (if not OTU level). |
include |
Parameters to include in prediction. |
C |
Value for which difference function has to be larger or smaller than (default 0). |
B |
Number of permutations to perform |
norm |
When aggregating counts to normalize or not. |
log |
Log2 transform. |
sl |
Scaling value. |
featureOrder |
Hierarchy of levels in taxonomy as fData colnames |
... |
Options for ssanova |
List of matrix of time point intervals of interest, Difference in abundance area and p-value, fit, area permutations, and call.
A list of objects including:
timeIntervals - Matrix of time point intervals of interest, area of differential abundance, and pvalue.
data - Data frame of abundance, class indicator, time, and id input.
fit - Data frame of fitted values of the difference in abundance, standard error estimates and timepoints interpolated over.
perm - Differential abundance area estimates for each permutation.
call - Function call.
cumNorm
ssFit
ssIntervalCandidate
ssPerm
ssPermAnalysis
plotTimeSeries
data(mouseData) res = fitSSTimeSeries(obj=mouseData,feature="Actinobacteria", class="status",id="mouseID",time="relativeTime",lvl='class',B=2)