Next Article in Journal
Identifying Potential Regions of Copy Number Variation for Bipolar Disorder
Previous Article in Journal
Copy Number Variation in Chickens: A Review and Future Prospects
Article Menu

Export Article

Open AccessArticle
Microarrays 2014, 3(1), 39-51; doi:10.3390/microarrays3010039

Comparative Analysis of Biologically Relevant Response Curves in Gene Expression Experiments: Heteromorphy, Heterochrony, and Heterometry

Biometry Research Group, National Cancer Institute, Bethesda, MD 20872, USA
Received: 20 December 2013 / Revised: 7 February 2014 / Accepted: 11 February 2014 / Published: 14 February 2014
View Full-Text   |   Download PDF [224 KB, uploaded 14 February 2014]   |  

Abstract

To gain biological insights, investigators sometimes compare sequences of gene expression measurements under two scenarios (such as two drugs or species). For this situation, we developed an algorithm to fit, identify, and compare biologically relevant response curves in terms of heteromorphy (different curves), heterochrony (different transition times), and heterometry (different magnitudes). The curves are flat, linear, sigmoid, hockey-stick (sigmoid missing a steady state), transient (sigmoid missing two steady states), impulse (with peak or trough), step (with intermediate-level plateau), impulse+ (impulse with an extra parameter), step+ (step with an extra parameter), further characterized by upward or downward trend. To reduce overfitting, we fit the curves to every other response, evaluated the fit in the remaining responses, and identified the most parsimonious curves that yielded a good fit. We measured goodness of fit using a statistic comparable over different genes, namely the square root of the mean squared prediction error as a percentage of the range of responses, which we call the relative prediction error (RPE). We illustrated the algorithm using data on gene expression at 14 times in the embryonic development in two species of frogs. Software written in Mathematica is freely available.
Keywords: double sigmoid; microarray; relative prediction error; sigmoid; time series double sigmoid; microarray; relative prediction error; sigmoid; time series
Figures

This is an open access article distributed under the Creative Commons Attribution License (CC BY 3.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Baker, S.G. Comparative Analysis of Biologically Relevant Response Curves in Gene Expression Experiments: Heteromorphy, Heterochrony, and Heterometry. Microarrays 2014, 3, 39-51.

Show more citation formats Show less citations formats

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Microarrays EISSN 2076-3905 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top