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PDAP: Phenotypic Diversity Analysis Programs

PDAP: PHENOTYPIC DIVERSITY ANALYSIS PROGRAMS

PDAP: PHENOTYPIC DIVERSITY ANALYSIS PROGRAMS
Version 6.0 Copyright March 2002 by
Theodore Garland, Jr., Peter E. Midford, Jason A. Jones,
Allan W. Dickerman, and Ramon Diaz-Uriarte
Development of these programs was supported by
National Science Foundation grants to T.G. (BSR-9006083, BSR-9146864 [REU],
IBN-9157268 [PYI], DEB-9220872, DEB-9509343, DEB-0196384)

Most recent updates are September 2004

PDAP is a set of Microsoft DOS computer programs, but they will run fine in a DOS window under Windows 95/98, Windows XP or Linux.  PDAP is distributed free of charge.  PDAP is not copy protected, and permission is hereby granted to duplicate it, provided that the above copyright information is not deleted.  Version 1.0 of PDAP accompanied:

Garland, T., Jr., A. W. Dickerman, C. M. Janis, and J. A. Jones. 1993.
     Phylogenetic analysis of covariance by computer simulation.
     Systematic Biology 42:265-292. [PDF file]

Please cite the foregoing paper with respect to these programs in general, but note that the various features and modules were added subsequently.  For example, the squared-change parsimony program PDSQCHP accompanied (Garland et al., 1997) and the independent contrasts module of PDTREE should cite Garland et al. (1999) and Garland and Ives (2000):

Garland, T., Jr, P. E. Midford, and A. R. Ives. 1999. An introduction to phylogenetically based
     statistical methods, with a new method for confidence intervals on ancestral states.
     American Zoologist 39:374-388. [PDF file]

Garland, T., Jr., and A. R. Ives. 2000. Using the past to predict the present:
     Confidence intervals for regression equations in phylogenetic comparative methods.
     American Naturalist 155:346-364. [PDF file]

For questions about these programs or to obtain a copy, including documentation and references, contact:

Theodore Garland, Jr.
Department of Biology
University of California, Riverside
Riverside, CA 92521
U.S.A.
Office telephone:  (951) 827-3524
Facsimile:  (951) 827-4286
E-mail:  tgarland@ucr.edu

PDAP is generally distributed in two forms.  First, I can email it as an attachment, PDAP.EXE, which is self-extracting (i.e., just type "PDAP" and it will "explode" into the original files (i.e., sources code, executable programs, documentation, example data sets).  Second, I can send PDAP on a high-density (1.44 mb) 3.5" DOS-formatted disk.  We are constantly updating and adding to these programs, so if you are going to use them then it is best to get the latest versions directly from me.  I also distribute the CMAP programs of Martins and Garland (1991), although they have been almost completely superseded by PDAP.

We are currently working on porting some of the PDAP modules (PDTREE for starters) into the Mesquite package of Wayne and David Maddison.  Mesquite and the PDTREE module are available at:
http://mesquiteproject.org/pdap_mesquite/index.html

A separate package of programs, PHYLOGR, produced by Ramon-Diaz-Uriarte and T.G., is available at http://cran.r-project.org/PHYLOGR is written in the free "R" language, and analyzes comparative data via Monte Carlo simulations or generalized least-squares approaches.  The package accompanies Díaz-Uriarte and Garland (in revision).  R is free, open-source software (similar to S+), available from the Comprehensive R Archive Network at http://cran.r-project.org and mirror sites.  As with other R packages, PHYLOGR is available available from CRAN in source code (tar.gz format) and as a zip file for Windows systems.  Installation is the same as for any other package (see Appendix 1 in our manuscript).

PHYSIG, a set of MatLab programs to test for and quantify the amount of phylogenetic signal in comparative data, are described here:

Blomberg, S. P., T. Garland, Jr., and A. R. Ives. 2003. Testing for phylogenetic signal in comparative data: behavioral traits are more labile. Evolution 57:717-745.  [PDF file]

and can be obtained form T.G. An overview is here: http://www.biology.ucr.edu/people/faculty/Garland/PHYSIG.html

 

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II. INTRODUCTION AND OVERVIEW OF PDAP
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    Version 6.0 of this software is a set of several programs, collectively termed the Phenotypic Diversity Analysis Programs (PDAP).  To start a program, simply
type its name at the DOS prompt.  The modules are designed to be used together to perform certain types of phylogenetically based statistical analyses of comparative data.  All of the programs are designed to deal with two traits at once.  More than two traits can be analyzed by running them two at a time and then merging output files and entering them into a commercial statistics/graphics package.  PDAP supersedes essentially all of the functions in the Comparative Method Analysis Program (CMAP) of Martins and Garland (1991; applications of CMAP can be found in: Garland et al., 1991; Garland, 1992; Garland et al., 1992; Walton, 1993; Garland and Janis, 1993; Garland et al., 1993; Garland and Adolph, 1994).  All of these programs have been written in Borland's Turbo Pascal and will run on MS-DOS machines, as well as in a DOS window under Windows 95/98 or Windows XP.  PDTREE and PDSIMUL require an EGA or VGA monitor (the former may do strange things with EGA).  PDAP was compiled in Turbo Pascal 6.0; both ASCII source code files (*.PAS) and compiled versions (*.EXE) are distributed at no cost.

PDTREE allows the user to enter and edit a phylogenetic tree and associated phenotypic data for the species at its tips.  The data for the species at the tips (henceforth called tip data), the tree topology, and the branch lengths can be independently adjusted or transformed in many ways.  Tree editing is graphic and very flexible.  All files used by PDTREE (and all other PDAP modules) are plain ASCII text.  PDTREE can save tree/data files in various formats, including the .PDI format that we often use in PDAP, the .INP format for CMAP modules (Martins and Garland, 1991), and the bracket format (.BRK) used by MacClade, PAUP, PHYLIP, and many other programs.

PDTREE also analyzes data by the method of phylogenetically independent contrasts (Felsenstein, 1985), and includes a series of diagnostics to check assumptions of this method (see also Garland, 1992, 1994; Garland et al., 1991, 1992, 1993; Garland and Janis, 1993; Garland and Adolph, 1994; Diaz-Uriarte and Garland, 1996, 1998).  It can output an ASCII file of the independent contrasts (.FIC) and their associated standard deviations (plus the nodal values used during computation of the contrasts), as well as an ASCII file containing these plus a variety of associated statistics for the two phenotypic traits.  Using independent contrasts, PDTREE also allows estimation of ancestral states (values at internal nodes or at any point along a branch) and their standard errors (Garland et al., 1999), as well as regression equations, confidence intervals, and prediction intervals mapped back onto the original data space (Garland and Ives, 2000).  Garland and Ives (2000) demonstrate the formal mathematical and statistical equivalency of independent contrasts and generalized least-squares (GLS) models (e.g., see Martins and Hansen, 1997; Pagel, 1998).

PDSINGLE is used to perform analysis of (co)variance (AN[C]OVA) on one set of data.

PDANOVA is like PDSINGLE, but is used to analyze many sets of simulated data.  The simulated data can come from the present PDSIMUL or from CMSIMUL of Martins and Garland (1991); they could also come from PDRANDOM.

PDSIMUL simulates the possibly correlated evolution of two traits up a user-specified phylogenetic tree.  PDSIMUL allows for numerous evolutionary models and associated parameters to be specified by the user (e.g., Garland et al., 1993; Diaz-Uriarte and Garland, 1996).

PDSIMMOD modifies the tip data in the files produced by PDSIMUL.  It is mainly a research tool, and has not yet been used in any publications (as of 20 August 2004).  One use would be to determine the statistical power for comparing mean values of different groups of species, abnother would be in tests of convergent evolution.

PDSQCHP estimates the values of internal nodes (hypothetical ancestors), including the root (basal) node, by use of weighted squared-change parsimony (see Huey and Bennett, 1987; Losos, 1990; Maddison, 1991; Martins and Garland, 1991; Maddison and Maddison, 1992; McArdle and Rodrigo, 1994; Westneat, 1995a,b; Miles and Dunham, 1996; Garland et al., 1997).  These values are the same as those produced by maximum likelihood under a Brownian motion assumption (Schluter et al., 1997; see also Garland et al., 1999).  PDSQCHP can also be used to compute the evolutionary correlation between two characters, i.e., ME1G or ME1P of the CMSINGLE program of Martins and Garland (1991).  Unlike CMSINGLE, however, PDSQCHP will accept phylogenies with hard polytomies.

PDDIST creates distance matrices from phylogenetic trees produced by the PDTREE program. The program reads a file of phylogeny and tip data (e.g., in the .PDI format) and then writes distance matrices that can be used in other PDAP modules or in other programs.  Five different kinds of distance matrices can be produced.  One of these, with the .DSC extension, is the same as used in Generalized Least Squares models (e.g., the V matrix of Garland and Ives, 2000).

PDERROR was designed initially as a research tool (Diaz-Uriarte and Garland, 1996, 1998; Garland and Diaz-Uriarte, 1999).  However, it can also be used simply to obtain independent contrast statistics for a set of simulated data (from PDSIMUL or PDRANDOM), whether or not you request any of the various branch-length tweaks or transformations that it implements. PDERROR can also rank or categorize the tip data before computing contrasts.  In combination with PDSIMUL (or RDRANDOM), PDERROR could be used to test for directional trends in character evolution.

PDTIPS performs a variety of conventional statistical operations on simulated tip data (i.e., a *.SIM file produced by PDSIMUL), such as a simple Pearson product-moment correlation; thus, it supersedes CMTPANAL.  It can also categorize the tip data before computing statistics, or transform the tip data with the Box-Cox procedure (to improve normality), and it can write a new version of the *.SIM file that contains the transformed tip data.  Like PDERROR, it is a research tool that can also be used for creating computer-simulated (or randomized) null distributions for hypothesis testing (e.g., see Lapointe and Garland, 2001).

RDRANDOM accompanied Lapointe and Garland (2001).  It accepts a PDI (or other format) file as input, and then performs conventional (equiprobable) or phylogenetic (probabilistic) permutations (randomizations) of the tip data.  The latter constitutes a new approach to the creation of "phylogenetically correct" null distributions.  Hence, PDRANDOM can be thought of as an alternative to PDSIMUL.  We would welcome comments from users.

RDNEXUS PDNEXUS.EXE allows one to read in Nexus files (Maddison et al., 1997) and save them out as PDI files.

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