In jaleesr/TrendCatcher_1.0.0: TrendCatcher: A Versitile R package for analyse longitudinal RNA-seq study

1. Load TrendCatcher R package.

library(TrendCatcher)

2. Read in the demo count table.

TrendCatcher requires the input count table in CSV file and with the column name in format as "ProjectName_Time_Rep1". And the first column as gene symbol or gene ensembl ID.

example.file.path<-system.file("extdata", "Brain_DemoCountTable.csv", package = "TrendCatcher")
tb<-read.csv(example.file.path, row.names = 1)
head(tb)

3. Run TrendCatcher and generate master.list object

This function will take few minutes to finish running with multiple cores.

example.file.path<-system.file("extdata", "Brain_DemoCountTable.csv", package = "TrendCatcher")

master.list<-run_TrendCatcher(count.table.path = example.file.path,
baseline.t = 0,
time.unit = "h",
min.low.count = 1,
para.core.n = NA,
dyn.p.thres = 0.05)

4. Check master.list in detail.

To save time of running, we already put the output master.list object in the '/inst/extdata' folder. You can simply load it into your environment.

demo.master.list.path<-system.file("extdata", "BrainMasterList.rda", package = "TrendCatcher")
load(demo.master.list.path)

First, check what elements are included in the master.list list object.

names(master.list)

• "time.unit" is the time unit, for example "h" represents hour.
• "baseline.t" is the baseline time. Here it is hour 0.
• "t.arr" is the time array in time course study. Here is 0, 6, 24, 48, 72, 168h.
• "Project.name" is the project name. Here is "B".
• "raw.df" is the count table ordered by time and replicate ID.
• "fitted.count" is the ANOVA smooth model fitted count number from replicates.

print(c(master.list$time.unit, master.list$baseline.t))

master.list$t.arr

master.list$Project.name

head(master.list$raw.df)

The fitted.count table each column represents.

• Gene, gene ensembl ID or gene symbol from the raw data.
• Time, time measured.
• Fit.Count, the ANOVA smooth model fitted count value.
• mu, the estimated mean count of baseline expression.
• disp, dispersion estimated of the baseline expression.
• t.p.val, the dynamic p-value at each time point compared to baseline NB distribution.
• dyn.p.val, the combined dynamic p-value from all time points.
• dyn.p.val.adj, the adjusted dynamic p-value from all DDEGs.

head(master.list$fitted.count)

For the master table, each column represents.

• Gene, gene ensembl ID or gene symbol.
• pattern, the gene trajectory master-pattern type.
• start.idx, the index of where the corresponding trend start in t.arr.
• end.idx, the index of where the corresponding trend end in the t.arr.
• dynTime, the time where t.p.val <=0.05, the break point.
• dynSign, "-" means down, "+" means up.
• start.t, the time of where the corresponding trend start.
• end.t, the time of where the corresponding trend end.
• pattern_str, the string ready for print indicates the gene trajectory sub-pattern type.

head(master.list$master.table)

jaleesr/TrendCatcher_1.0.0 documentation built on Jan. 29, 2024, 9:34 p.m.