Fisher's Exact with mid-P method 1.0

It is a non-parametric statistical test for discrete data used todetermine if there are nonrandom associations between the two variables.Mid-P values are a reasonable compromise between the conservativeness ofthe ordinary exact test and the uncertain adequacy of large-sample methods.Mid-P values usually performs well, typically being a bit conservative,and is currently recommended by many leading statisticians.Ref.: DeltaProt toolbox at http://services.cbu.uib.no/software/deltaprot/Input:X: data matrix (2x2-table) of observed countstail: The alternative hypothesis against which to compute p-values.Choices are: 'ne' 2-Tail (default) 'gt' Right tail: the alternative to independence is that there is positive association between the variables. 'lt' Left tail: the alternative hypothesis is that there is negative association between the variablesOutput: P-valueUse: P = FisherExtest(Observed,'ne')Please, use the following reference:Thorvaldsen, S. , FldoDE, T. and Willassen, N.P. (2010) DeltaProt: a software toolbox for comparative genomics. BMC Bioinformatics 2010, Vol 11:573.See http://www.biomedcentral.com/1471-2105/11/573Other references:Agresti, A. (2001), Exact inference for categorical data: recent advances and continuing controvercies. Statistics in Medicine, 20: 2709-2722.Hirji, K.F. (2006), Exact Analysis of Discrete Data. Chapman & Hall.Fisher, R.A. (1934), Statistical Methods for Research Workers. Chapter 12. 5th Ed., Oliver & Boyd.

Requirements:	No special requirements
Platforms:	Matlab
Keyword:	Bioinformatics,  Comparative,  Genomics,  Reference,  References,  Software,  Thorvaldsen,  Willassen
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