metalonda: Metagenomic Longitudinal Differential Abundance Analysis for...

In aametwally/MetaLonDA: Metagenomics Longitudinal Differential Abundance Method

Description

Find significant time intervals of the one feature

Usage

metalonda(
  Count,
  Time,
  Group,
  ID,
  n.perm = 500,
  fit.method = "nbinomial",
  points,
  text = 0,
  parall = FALSE,
  pvalue.threshold = 0.05,
  adjust.method = "BH",
  time.unit = "days",
  ylabel = "Normalized Count",
  col = c("blue", "firebrick"),
  prefix = "Test"
)

Arguments

Count	matrix has the number of reads that mapped to each feature in each sample.
Time	vector of the time label of each sample.
Group	vector of the group label of each sample.
ID	vector of the subject ID label of each sample.
n.perm	number of permutations.
fit.method	fitting method (nbinomial, lowess).
points	points at which the prediction should happen.
text	Feature's name.
parall	boolean to indicate whether to use multicore.
pvalue.threshold	p-value threshold cutoff for identifing significant time intervals.
adjust.method	multiple testing correction method.
time.unit	time unit used in the Time vector (hours, days, weeks, months, etc.)
ylabel	text to be shown on the y-axis of all generated figures (default: "Normalized Count")
col	two color to be used for the two groups (eg., c("red", "blue")).
prefix	prefix to be used to create directory for the analysis results

Value

returns a list of the significant time intervals for the tested feature.

References

Ahmed Metwally ([e-mail])

Examples

data(metalonda_test_data)
n.sample = 5
n.timepoints = 10
n.group = 2
Group = factor(c(rep(0, n.sample*n.timepoints), rep(1,n.sample*n.timepoints)))
Time = rep(rep(1:n.timepoints, times = n.sample), 2)
ID = factor(rep(1:(2*n.sample), each = n.timepoints))
points = seq(1, 10, length.out = 10)
## Not run: 
output.nbinomial = metalonda(Count = metalonda_test_data[1,], Time = Time, Group = Group,
ID = ID, fit.method =  "nbinomial", n.perm = 10, points = points,
text = rownames(metalonda_test_data)[1], parall = FALSE, pvalue.threshold = 0.05, 
adjust.method = "BH", time.unit = "hours", ylabel = "Normalized Count", col = c("black", "green"))

## End(Not run)

aametwally/MetaLonDA documentation built on Dec. 26, 2019, 7:46 a.m.