eq.test: Test of Equality of Circular Orders

In isocir: Isotonic Inference for Circular Data

Test of Equality of Circular Orders

Description

This function calculates the test of equality of circular orders in different populations.

Usage

eq.test(data, popu, ws=NULL, method=NULL, control.method=NULL, output=NULL, coef=1, N=500)

Arguments

data	matrix or data.frame with the data. See details.
popu	a numeric vector with population to each experiment belongs.
ws	a numeric vector with the values to be used as weight per experiment.
method	The method to be used to aggregate circular orders with ACO function.
control.method	The argument to control the method in ACO function.
output	The path where write the output of the global orders.
coef	The coefficient to use in case of method=TSP, by default 1.
N	The number of randomization selections, by default 500.

Details

This function performs the test to constrast equality of circular orders:

\hspace{1.7cm}H_{0}: The circular parameters follow the same circular order in all populations.

\hspace{1.7cm}H_{1}:\hspace{0.1cm}H_{0} is not true.

The data must have the elements in the columns and the experiments in the rows.

Value

The output is a list with the following values:

allorders	matrix, in each row the circular order obtained with all selected experiments and the value for the statistic test in that selection.
pvalue	numeric, it is the p-value what results of the test.
global_order	numeric vector with the elements ordered as the global circular order estimate.
CC	numeric, the confidence coefficient (in percentage) of the global order.
MFO	numeric vector with the elements ordered as the Most Frequent global Order in the randomization procedure.
CCMFO	numeric, the confidence coefficient (in percentage) of the Most Frequent global Order.

Two additional outputs could be obtained in the form of .csv files written in the path given by the user in the argument output:

globalorders.csv	all the global orders obtained from the randomization procedure and the value of the statistic in each selection.
frequencydist.csv	the frequency distribution of all the global orders.

Author(s)

Author(s): Sandra Barrag?n. Maintainer:<[e-mail]>

References

Rueda, C., Fernandez, M. A. and Peddada, S. D. (2009). Estimation of parameters subject to order restrictions on a circle with application to estimation of phase angles of cell-cycle genes. Journal of the American Statistical Association, 104, n485; pp 338–347. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2742472/

Fernandez, M. A., Rueda, C. and Peddada, S. D. (2012). Identification of a core set of signature cell cycle genes whose relative order of time to peak expression is conserved across species, Nucl. Acids Res. 40, n7: pp 2823–2832. doi:10.1093/nar/gkr1077. https://academic.oup.com/nar/article/40/7/2823/1183140

Barragan, S., Rueda, C., Fernandez, M.A. and Peddada, S.D. (2015). Determination of Temporal Order among the Components of an Oscillatory System. PLOS ONE. 10, n7: pp 1–14. doi: 10.1371/journal.pone.0124842. https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4495067/

See Also

ACO, CIRE,sce, mrl, isocir, plot.isocir.

Examples

data(cirgenes)
eq.test(cirgenes[-8,c(1:5)], popu=c(rep(1,5),rep(2,4)),
ws=c(1,2,3.5,2,1,8,4.2,1.35,6), method="TSP",control.method="alpha3",N=2)

isocir documentation built on Aug. 17, 2023, 9:07 a.m.