RE: [MORPHMET] Problems visualizing curves across versions of tpsDig

2017-02-23 Thread F. James Rohlf 
This is most likely caused by not setting the decimal character (. Or ,) to 
agree with what is used in the tps file.

 



F. James Rohlf, Distinguished Professor, Emeritus. Ecology & Evolution

Research Professor, Anthropology

Stony Brook University

 

From: Luis Ruedas [mailto:rue...@pdx.edu] 
Sent: Tuesday, February 21, 2017 12:49 PM
To: morphmet@morphometrics.org
Subject: [MORPHMET] Problems visualizing curves across versions of tpsDig

 

 

I have been digitizing data from some 2D images on a computer where I had
loaded tpsDig 2.16 (yes, a long time ago, I know) then tried to work on a
laptop with tpsDig 2.29.  Initially, I was unable to see the curves I had
created.  When I changed to a high vis color, I noticed a thick line on the
bottom edge of the image in tpsDig.  The file remains unchanged, with the
original curve coordinates.

Anyone know what may be going on? Help is welcome...

All the best,

Luis

 

-- 


Luis A. Ruedas, Ph.D.
Associate Professor of Biology
Portland State University

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[MORPHMET] tpsdSuper update

2017-02-23 Thread F. James Rohlf 
I have just uploaded version 2.04 of tpsSuper to the
http://life.bio.sunysb.edu/morph server.

 

It fixes a problem in saving aligned specimens that was noticed by Jennifer
Valvo.

 



F. James Rohlf, Distinguished Professor, Emeritus. Ecology & Evolution

Research Professor, Anthropology

Stony Brook University

 

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[MORPHMET] Advancing in Statistical Modelling for evolutionary biologists and ecologists using R

2017-02-23 Thread Oliver Hooker 
"Advancing in Statistical Modelling for evolutionary biologists and 
ecologists using R"

Delivered by Dr. Luc Bussiere and Dr. Ane Timenes Laugen

*http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr06/*
 


This course will run from 24th - 28th April 2017 at SCENE field station, 
Loch Lomond, Glasgow

Course only and all inclusive packages are available.

This course will provide an introduction to working with real-life data 
typical of those encountered in the field of evolutionary biology and 
ecology. The course will be delivered by Dr. Luc Bussiere and Dr. Ane 
Timenes Laugen who are both practicing academics in the field of 
ecology.  This five day course will consist of series of modules (each 
lasting roughly half a day) covering model selection and simplification, 
generalised linear models, mixed effects models,  and non-linear models. 
Along the way you will gain in depth experience in data ‘wrangling’, data 
and model visualisation and plotting, as well as exploring and 
understanding model diagnostics. Classes will comprises of a mixture of 
lectures and practicals designed to either build required skills for future 
modules or to perform a family of analyses that is frequently encountered 
in the biological literature.

Course content is as follows

Day 1 Course introduction
• Techniques for data manipulation, aggregation, and visualisation; 
introduction to linear regression. Packages: {tidyr}, {dplyr}, {ggplot2}

Day 2 Linear models
• Diagnostics, collinearity, scaling, plotting fitted values); fitting and 
interpreting interaction terms; model selection and simplification; general 
linear models and ANCOVA.
• Packages: {stats}, {car}

Day 3 Generalized linear models
• Logistic and Poisson regression; predicting using model objects and 
visualizing model fits.
• Packages: {broom}, {visreg}, {ggplot2}

Day 4 Mixed effects models
• Theory and practice of mixed effect models; visualising fixed and random 
effects.
• Packages: {lme4}, {broom}, {ggplot2}, {sjPlot}

Day 5 Fitting nonlinear functions
• Polynomial & Mechanistic models; brief introduction to more advanced 
topics & combining methods (e.g., generalised linear mixed effects, 
nonlinear mixed effects, and zero-inflated and zero-altered models).
• Packages: {nlsTools}.
• Afternoon to discuss own data if time permits

Please email any inquiries to oliverhoo...@prstatistics.com or visit our 
website *www.prstatistics.com* 

Please feel free to distribute this material anywhere you feel is suitable

Our other courses

1. STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR #SIMM
28th Feb – 3rd Mar 2017, Scotland, Dr. Andrew Parnell, Dr. Andrew Jackson
*http://www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm03/*
 


2. NETWORK ANAYLSIS FOR ECOLOGISTS USING R #NTWA
6th – 10th March 2017, Scotland, Dr. Marco Scotti
*http://www.prstatistics.com/course/network-analysis-ecologists-ntwa01/* 


3. ADVANCES IN MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA USING R 
#MVSP
3rd – 7th April 2017, Scotland, Prof. Pierre Legendre, Dr. Olivier Gauthier
*http://www.prstatistics.com/course/advances-in-spatial-analysis-of-multivariate-ecological-data-theory-and-practice-mvsp02/*
 


4. ADVANCING IN STATISTICAL MODELLING FOR EVOLUTIONARY BIOLOGISTS AND 
ECOLOGISTS USING R #ADVR
17th – 21st April 2017, Scotland, Dr. Luc Bussiere, Dr. Ane Timenes Laugen
*http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr06/*
 


5. CODING, DATA MANAGEMENT AND SHINY APPLICATIONS USING RSTUDIO FOR 
EVOLUTIONARY BIOLOGISTS AND ECOLOGISTS #CDSR
15th - 19th May, Scotland Dr. Aline Quadros
*http://www.prstatistics.com/course/coding-data-management-and-shiny-applications-using-rstudio-for-evolutionary-biologists-and-ecologists-cdsr01/*
 


6. GEOMETRIC MORPHOMETRICS USING R #GMMR
5th – 9th June 2017, Scotland, Prof. Dean Adams, Prof. Michael Collyer, Dr. 
Antigoni Kaliontzopoulou
*http://www.prstatistics.com/course/geometric-morphometrics-using-r-gmmr01/* 


7. MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA #MASE
19th – 23rd June, Scotland, Prof. Subhash Lele, Dr. Peter Solymos
*http://www.prstatistics.com/course/multivariate-analysis-of-spatial-ecological-data-using-r-mase01/*

[MORPHMET] Coding, data management, and Shiny applications using RStudio for evolutionary biologists and ecolog

2017-02-23 Thread Oliver Hooker 
Coding, data management, and Shiny applications using RStudio for 
evolutionary biologists and ecologists (CDSR01)

*http://www.prstatistics.com/course/coding-data-management-and-shiny-applications-using-rstudio-for-evolutionary-biologists-and-ecologists-cdsr01/*
 


This course will run from the 15th - 19th May 2017 at SCENE field station, 
Loch Lomond, Scotland.

Course overview:
The course will introduce programming logic using the R syntax. The 
participants will be able to solve problems involving heterogeneous 
biological datasets and the combined use of different statistical packages, 
so the advantages of learning programming skills can be demonstrated. The 
RMarkdown syntax will be used to illustrate the advantages of literate 
programming and the possibilities of code sharing and archiving. In the 
sequence, participants will learn how to design relational databases (RDB) 
which can be used to manage and analyse large biological datasets. They 
will learn the basics of the SQL language and how to use it with R with the 
package {RMySQL}. To finalise, they will use the Shiny tool (R Studio) to 
build interactive applications to analyse and display data depending on 
user inputs. Throughout the course we will emphasise data, code and 
analyses best practices that could foster reproducibility and transparency 
in science, and the long-term availability of scientific data. At the end 
of the course the participants are expected to be able to develop small, 
tailored applications, to read and analyse datasets using a variety of 
statistics tools.

Intended Audience:
Researchers and postgraduate students working with in evolutionary biology 
and ecological data who want to have more autonomy and flexibility in their 
quantitative analyses, and need to access and analyse large datasets with R.

Monday 15th – Classes from 09:00 to 17:00
Module 1: Programming Logic
R syntax (Variable types – operators – conditionals – loops – writing 
functions)
Programming and commenting code with RMarkdown

Tuesday 16th – Classes from 09:00 to 17:00
Module 2: Data structures
R syntax (arrays, lists, data frames, matrices)
Data wrangling with {dplyr} and {tidyr}; the {ff} package and data tables 
for large datasets (e.g. transcriptomics; whole-genome data)
Best practices of data acquisition, organization and storage

Wednesday 17th – Classes from 09:00 to 17:00
Module 3: Relational databases
Introduction to the SQL language and MySQL (open-source RDB freeware)
Accessing and analysing large datasets using the package {RMySQL}
As an example, we will combine DNA sequence datasets with IUCN Red List 
data illustrate the use of RDB to biological datasets.

Thursday 18th – Classes from 09:00 to 17:00
Module 4: Introduction to Shiny (R Studio)
Shiny – Server and user interface commands
As an example we will use Shiny to develop a small application where users 
can select different species and genes and run/visualize phylogenetic trees 
using {ape} running in the background.

Friday 19th  – Classes from 09:00 to 16:00
Module 5: Wrapping-up
Development and presentation of individual projects combining data 
wrangling skills and user inputs using Shiny (R Studio)

Teaching Format:
The course will be highly practical, with a series of hands-on, 
step-by-step, problem-solving exercises, combining the different tools to 
solve ecological and evolutionary biology problems. The participants are 
invited to think of a problem that requires programming skills to be 
solved, and can bring their own data for a case-study. At the end of each 
day the participants will have time to work on their on projects and apply 
the skills learned on that day.

We offer two packages
COURSE ONLY – Includes lunch and refreshments.
ALL INCLUSIVE – Includes breakfast, lunch, dinner, refreshments, minibus to 
and from meeting point and accommodation. Accommodation is multiple 
occupancy (max 3 people) single sex en-suite rooms. Arrival Sunday 14th May 
and departure Friday 19th May PM.

Please send enquiries to oliverhoo...@prstatistics.com or visit 
*www.prstatistics.com*  for more details.

Other relevant upcoming courses are as follows

1. STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR #SIMM
28th Feb – 3rd Mar 2017, Scotland, Dr. Andrew Parnell, Dr. Andrew Jackson
*http://www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm03/*
 


2. NETWORK ANAYLSIS FOR ECOLOGISTS USING R #NTWA
6th – 10th March 2017, Scotland, Dr. Marco Scotti
*http://www.prstatistics.com/course/network-analysis-ecologists-ntwa01/* 


3. ADVANCES IN MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA USING R 
#MVSP
3rd – 7th April 2017,