I'm working on analysis of genetic diversity of P. vivax in Thailand by DNA sequencing using Illumina Miseq. Gene targets are polymorphic regions of PvMSP-1, PvAMA-1, PvCSP, and PvDBP (4 markers). The problem is how I can estimate the number of samples or isolates as a good representative of certain population. Are there any similar previous works I can look for? Thank you in advance.
well the point is: if you really want to be sure, do as much as you can and the time/budget allows, because only in the end you will know...
but a good approach is to get samples from an as much divert background as you can, sequence and see how big the differences are while making a statistics on how a certain difference appears. think also of the statistical error is a function of the square root of the sample size, so you see taking 100 samples with a clever distribution of origin, might be a good first shot, leaving the room for going to 500 or 1000 samples... so some approach like that also depending on the size of your markers in terms of: the bigger the more differences on a single NP you find...
The sample size depends on the type of your population, is it finite population or infinite population.
In the case of finite population, you can use the Slovin formula:
n= N / ( 1+ N * e^2 )
But in the case of an infinite population:
The sample size for any study depends on the standard deviation of the variable ( from previous studies ) and the margin of error you decided. The formula:
n= ( Z^2 * S^2) / E^2
where : Z ( 1.96 for 0.05 and 2.58 for 0.01 )
S = standard deviation from previous studies or pilot study
E = significant level
Also, you can use software to calculate sample size ( SPSS , Minitab , G*power )
My advice to use G*Power . G*Power software is effective tool to calculate sample size for many ranges of experiments. Also, you can determine effect size and power of the test, G*Power is free to download and easy to use after reading the manual, the download link:
http://download.cnet.com/G-Power/3000-2054_4-10647044.html
The link to download G*Power manual:
http://www.gpower.hhu.de/fileadmin/redaktion/Fakultaeten/Mathematisch-Naturwissenschaftliche_Fakultaet/Psychologie/AAP/gpower/GPowerManual.pdf
I hope that be useful for you.
Good Luck
I think you should follow related paper. Suppose there are using 500 individuals sample of 10 populations. You will be carried out 150 individual sample and 6 or 8 population but you know effective population that are varied each other.
Maybe a research article "SNeP: a tool to estimate trends in recent effective population size trajectories using genome-wide SNP data" can provide information that you want to!
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