Jhon, your formatting is confusing, please reformat your proposal, and try to describe in words what your function does. From what I could understand you are going to calculate descriptive statistics for each variable, is that it?

Hi Vitor,

The purpose of the function is to analyze the data so descriptive and exploratory.

input: table or data.frame containing the morphological dimensions (eleven) for each species.

John, please rewrite you proposals. they are appearing with strange characters for me, and the formatting is confusing.

Function

Input: table containing the morphological dimensions for each species (table.txt).

The purpose of the function is to analyze the data so descriptive and exploratory.

1) Mean and standard deviation of each species.

2) Testing the existence of differences between measurements for each species

1. Test normality

Normal (PCA)

	Not normal (KruscalWalis)

3) Make graphics PCA

4) Output – table with the descriptive information (means, variance and standard deviation), and graphics PCA.

This function could be very basic our very complex, depending on your file input. It is basically an application of the table() function, is that correct?

in general, please revise the formatting of your proposals so that we can understand better

Hi Vitor, This function differs from the table function (X). In my proposal the input file is a file in FASTA format, which contains the sequence for each species (http://www.ncbi.nlm.nih.gov/BLAST/blastcgihelp.shtml). Executing this function will be known frequencies of purines (“A” and “G”) and pyrimidines (“C” and “T”) in each input files (species).

Input: file in FASTA format containing the sequence of DNA (js_2.txt).

The purpose of the function knows the percentage of purines (A“ and “G”) and pyrimidine (“C” and “T”) in DNA sequence of different taxas.

First function:

1) Sum the amount of purines (“A” and “G”) that occur along a DNA sequence. 2) Divide this sum over the total bases containing the DNA sequence and multiplies this value by 100. 3) Make graphics (Histograms showing results)

Second function:

1) Sum the amount of pyrimidine (“C” and “T”) that occurs along a DNA sequence. 2) Divide this sum over the total bases containing the DNA sequence and multiplies this value by 100. 3) Make graphics (Histograms showing results)

John, both your functions are very simplistic, unless you intend to code analyses by hand, and not simply call functions which do analyses for you, especially the first one. ALso, if you are going to do an “automated” analysis, you really should test for the other premisses of both ANOVA and PCA, normality is not the only one. The second one is just an aplicatio of the table() function on a string of characters, unless you decide to do the counting by hand, again.