Signal-to-noise statistic

In mathematics the signal-to-noise statistic distance between two vectors a and b with mean values $\mu _{a}$ and $\mu _{b}$ and standard deviation $\sigma _{a}$ and $\sigma _{b}$ respectively is:

D_{sn}={(\mu _{a}-\mu _{b}) \over (\sigma _{a}+\sigma _{b})}

This distance is frequently used to identify vectors that have significant difference. One usage is in bioinformatics to locate genes that are differential expressed on microarray experiments ^[1].

Notes

^ Pomeroy, S.L. et al. Gene Expression-Based Classification and Outcome Prediction of Central Nervous System Embryonal Tumors. Nature 415, 436–442.

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[1] Pomeroy, S.L. et al. Gene Expression-Based Classification and Outcome Prediction of Central Nervous System Embryonal Tumors. Nature 415, 436–442.

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See also

Notes