In the past several years the number of harmful algal blooms has been dramatically increasing. In fact, a recent bloom of Microcystis aeruginosa, known for its secretion of the hepatotoxin microcystin, has threatened the water supply of Lake Erie cities such as Toledo and Cleveland. An EPA friend wishes to study this species in order to prevent such blooms, and in so doing, finds significant heterogeneity in gene expression in clonal algal cells (same species, identical DNA) in the same environment! There is one order of magnitude of variation in certain transcription factors and two orders of magnitude of variation in lipid content. Recognizing your expertise your friend asks you for advice: Is this result reasonable or was this likely due to experimental error? How would one go about testing and explaining the results? Provide an answer to your colleague. Solution To study gene expression , since a long time, Microarray technology is being used in order to study more number of genes in a single experiment. This is then interpreted using significance analysis of transcriptomic data, but the disadvantage here lies that it would ignore gene dependence structure. Therefore , along with microarray technology for studying heterogeneity, FAMT would allow to capture gene dependence as a factor of computation of results. FAMT: Factor Analysis for Multiple Testing (FAMT) : is defined as simultaneous tests under dependence in high-dimensional data. It takes into account various factors to give high throughput data and accurate results. In FAMT, effects of the experimental conditions and the nuisance variability on gene expression, due to technical errors and other known or unknown effects, can be easily separated. The factors can be distinguished and interpreted using graphics. I am not aware of what protocol was followed by my colleague. Neither am I aware if the interfering signals were cancelled by the protocol followed. So rather, I would suggest to perform microarray for testing gene heterogeneity and interpreting the results using FAMT, so as to eliminate all sorts of interfering signals/ factors and also handling errors , if some. Results can be interpreted later after elimination of any error possibilities..

1. In the past several years the number of harmful algal blooms has been dramatically increasing.
In fact, a recent bloom of Microcystis aeruginosa, known for its secretion of the hepatotoxin
microcystin, has threatened the water supply of Lake Erie cities such as Toledo and Cleveland.
An EPA friend wishes to study this species in order to prevent such blooms, and in so doing,
finds significant heterogeneity in gene expression in clonal algal cells (same species, identical
DNA) in the same environment! There is one order of magnitude of variation in certain
transcription factors and two orders of magnitude of variation in lipid content. Recognizing your
expertise your friend asks you for advice: Is this result reasonable or was this likely due to
experimental error? How would one go about testing and explaining the results? Provide an
answer to your colleague.
Solution
To study gene expression , since a long time, Microarray technology is being used in order to
study more number of genes in a single experiment. This is then interpreted using significance
analysis of transcriptomic data, but the disadvantage here lies that it would ignore gene
dependence structure. Therefore , along with microarray technology for studying heterogeneity,
FAMT would allow to capture gene dependence as a factor of computation of results.
FAMT: Factor Analysis for Multiple Testing (FAMT) : is defined as simultaneous tests under
dependence in high-dimensional data. It takes into account various factors to give high
throughput data and accurate results. In FAMT, effects of the experimental conditions and the
nuisance variability on gene expression, due to technical errors and other known or unknown
effects, can be easily separated. The factors can be distinguished and interpreted using graphics.
I am not aware of what protocol was followed by my colleague. Neither am I aware if the
interfering signals were cancelled by the protocol followed. So rather, I would suggest to
perform microarray for testing gene heterogeneity and interpreting the results using FAMT, so as
to eliminate all sorts of interfering signals/ factors and also handling errors , if some. Results can
be interpreted later after elimination of any error possibilities.