Exploration, quantification, and mitigation of systematic error in high-throughput approaches to gene-expression profiling: implications for data reproducibility
View/ Open
Date
23/11/2011Author
Kitchen, Robert Raymond
Metadata
Abstract
Technological and methodological advances in the fields of medical and life-sciences
have, over the last 25 years, revolutionised the way in which cellular activity is measured
at the molecular level. Three such advances have provided a means of accurately
and rapidly quantifying mRNA, from the development of quantitative Polymerase
Chain Reaction (qPCR), to DNA microarrays, and second-generation RNA-sequencing
(RNA-seq). Despite consistent improvements in measurement precision and sample
throughput, the data generated continue to be a ffected by high levels of variability
due to the use of biologically distinct experimental subjects, practical restrictions
necessitating the use of small sample sizes, and technical noise introduced during
frequently complex sample preparation and analysis procedures. A series of experiments
were performed during this project to pro le sources of technical noise in each of these
three techniques, with the aim of using the information to produce more accurate and
more reliable results.
The mechanisms for the introduction of confounding noise in these experiments
are highly unpredictable. The variance structure of a qPCR experiment, for example,
depends on the particular tissue-type and gene under assessment while expression data
obtained by microarray can be greatly influenced by the day on which each array was
processed and scanned. RNA-seq, on the other hand, produces data that appear very
consistent in terms of differences between technical replicates, however there exist large
differences when results are compared against those reported by microarray, which
require careful interpretation.
It is demonstrated in this thesis that by quantifying some of the major sources of
noise in an experiment and utilising compensation mechanisms, either pre- or post-hoc,
researchers are better equipped to perform experiments that are more robust, more
accurate, and more consistent.
Collections
The following license files are associated with this item: