Abstract
There are many methods for selecting and clustering genes according to their time-course or dose-response profiles. These methods all necessitate the assumption of a constant variance through time or among dosages. This homoscedasticity assumption is, however, seldom satisfied in practice. In this paper, via the application of Shi’s (1994,1998) algorithms and a modified bootstrap procedure, we proposed a generalized order-restricted inference methodology for the same task without the homoscedasticity restriction. Simulation results show that our procedure can control the false positive rate and have some good qualities.
Highlights
In microarray experiments and dose-response studies, experimental conditions usually have some inherent orderings
Let Yigt denote the ith expression measurement taken on gene g at time point t, Ygt denote the sample mean of gene g at time point t and Yg (Yg1,Yg2,...,YgT )c
We carry out the test procedure (4) where the alternative hypothesis is the union of the following six profiles: monotone decreasing C1, monotone increasing C6, two up-down profiles with maxima at 2, 3 hours C2, C3, respectively; and two down-up profiles with minima at 2, 3 hours C4, C5, respectively
Summary
In microarray experiments and dose-response studies, experimental conditions usually have some inherent orderings. Order restricted statistical inference is an efficient tool to use these ordering information. Depending on the particular practical situation, one can use different order restricted methodologies. Suppose there are T time points denoted by1, 2,...,T , and at each time point there are nt observations, for each of G genes. Let Yigt denote the ith expression measurement taken on gene g at time point t , Ygt denote the sample mean of gene g at time point t and Yg (Yg1,Yg2 ,...,YgT )c. The unknown true mean expression level of gene g is (Pg1,..., PgT )c which is restricted by some partial ordering, where E(Ygt ) Pgt. Inequalities between the components of Pg (Pg1, Pg2 ,..., PgT )c define the true profile for gene g
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
