In cluster analysis of microarray data– If Xi is the log odds value for gene X at time i, then for two genes X and Y and N observations, a similarity score is calculated. S(X,Y) is also known as the Pearson correlation coefficent. Xoffset and Yoffset can be the mean of the observations on X or Y, respectively, in which case is the standard deviation, or else Xoffset and Yoffset can be set to zero when a reference state is used. Which of the following best represents it?(a) S(X,Y) = \(\frac{1}{N-2}\) ∑i=1,N . (Xi – Xoffset) (Yi + Yoffset)/ϕxQY(b) S(X,Y) = \(\frac{1}{N}\) ∑i=1,N . (Xi – Xoffset) (Yi – Yoffset)/ϕxQY(c) S(X,Y) = \(\frac{1}{N-1}\) ∑i=1,N . (Xi + Xoffset) (Yi + Yoffset)/ϕxQY(d) S(X,Y) = \(\frac{1}{N}\) ∑i=1,N+2 . (Xi + Xoffset) (Yi – Yoffset)/ϕxQYThe question was asked in an internship interview.This intriguing question comes from Global Gene Regulation in section Genome Analysis of Bioinformatics

In cluster analysis of microarray data– If Xi is the log odds value

1.	In cluster analysis of microarray data– If Xi is the log odds value for gene X at time i, then for two genes X and Y and N observations, a similarity score is calculated. S(X,Y) is also known as the Pearson correlation coefficent. Xoffset and Yoffset can be the mean of the observations on X or Y, respectively, in which case is the standard deviation, or else Xoffset and Yoffset can be set to zero when a reference state is used. Which of the following best represents it?(a) S(X,Y) = \(\frac{1}{N-2}\) ∑i=1,N . (Xi – Xoffset) (Yi + Yoffset)/ϕxQY(b) S(X,Y) = \(\frac{1}{N}\) ∑i=1,N . (Xi – Xoffset) (Yi – Yoffset)/ϕxQY(c) S(X,Y) = \(\frac{1}{N-1}\) ∑i=1,N . (Xi + Xoffset) (Yi + Yoffset)/ϕxQY(d) S(X,Y) = \(\frac{1}{N}\) ∑i=1,N+2 . (Xi + Xoffset) (Yi – Yoffset)/ϕxQYThe question was asked in an internship interview.This intriguing question comes from Global Gene Regulation in section Genome Analysis of Bioinformatics
Answer» The correct option is (b) S(X,Y) = \(\frac{1}{N}\) ∑i=1,N . (Xi – Xoffset) (Yi – YOFFSET)/ϕxQY The explanation: After values of S(X,Y) have been calculated for all gene combinations, the most closely related pairs are identified in an above-diagonal scoring matrix. The object of CLUSTERING is to identify GENES that RESPOND the same way to the environmental treatment. Each gene is compared to every other gene and a gene similarity score (metric) is produced.

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