Features of “PAD” (“Permutaciones, Analisis Discriminante”)
- Performs Discriminant analyses with limited graphical display (button “Mapa factorial“)
- Computation is based on the inverse of the consensus covariance matrix
- Factor map of the first two discriminant factors (DF1,DF2) only
- Respective contributions of each discriminant factor
- Table of Mahalanobis distances, formatted as for PHYLIP (J. Felsenstein) tree construction.
- Permutation of individuals among groups (button “Permutar distancias ?“)
- Random permutation of individuals in the total sample is used as a method to randomly interchange individuals among groups
- At each iteration, a complete discriminant analysis is performed
- As an estimate of statistical significance for each Mahalanobis distance, a proportion is given which is the number of Mahalanobis distances values equal or higher than observed, relative to the total number of permutations.
- Size-free analysis (button “DISTANCES, or TRADITIONAL“)
- Input data MUST be log-transformed measurements
- Size-free variables are computed (row centered data)
- Principal components are derived from these size-free variables, called here “size-free components”
- The optimal number of size-free components is suggested in relation to local sample sizes
- A discriminant analysis is performed on this number of size-free components.
- Allometric residual may be examined on each of the two first discriminant factors.
- Coordinates of landmarks analysis (button “LANDMARKS, or GEOMETRIC“)
- Input data are always Partial Warps, they are used either without restriction (button “PW, option ‘Total’) or “partly” (button “PW, option ‘Part’), meaning that only a few first Relative Warps are used. Select that option when the number of PW is too high relative to the number of individuals in the smallest group.
- Thus, if the option “PW, option ‘Part’ is selected, Relative Warps are computed and a subset of them is suggested for subsequent analyses.
- Allometric residual may be examined on each of the two first discriminant factors, provided a file is opened containing corresponding ‘centroid sizes’ (CS).
- Supplementary data (button “Datos Externos“)
- External data may be called, contained in a FORMAT formatted file.
- Their position on the DF1/DF2 factor map is computed according to the first two discriminant factors, DF1 and DF2
- In case of two groups, supplementary data are visible on the histogram of discriminating classes(March 2009)
- Mahalanobis distances are computed between each external individual and each centroid of the discriminant model
- A classification table is given
- This procedure is NOT available anymore for PW data; for a shape based Mahalanobis classification of unknown individuals relative to 2 or more groups, please use the MOG module.
- Reclassification of individuals (button “C“)
- This corresponds to the same sample being treated as external data
- Cross checked reclassification (button “CCC“).
- For each individual classification the individual itself is removed from the total sample, then:
– sample sizes are computed again;
– the Mahalanobis distances are computed between new centroids;
– the removed individual is then used as supplementary data, and its distance computed with each centroid;
– a re-classification table is contructed.
- External softwareis available (menu)
- The PHYLIP ‘neighbor’ and ‘fitch’ modules (J. Felsenstein) may be called directly from PAD; people wanting to use other modules of the PHYLIP package should go here.
- After answering the questions by the letters ‘N‘ (to obtain the UPGMA method instead of the Neighbor-Joigning one), ‘L‘ (lower diagoal matrix) and ‘Y‘ (yes) …
- … the PHYLIP outfile is directly printed within the PAD report.
- Each OTU is labeled as a number according to its order position in the input file. Giving a name to each OTU is possible by the menu “External Software” -> “Giving a name to each OTU”
- Direct access is also given to an editing tree software, njplot (see: Perriere, G. and Gouy, M. (1996) WWW-Query: An on-line retrieval system for biological sequence banks. Biochimie, 78, 364-369).
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