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BYU-Department
of Biology |
Biology 559R: Introduction to Phylogenetic Comparative
Methods
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Instructor |
Juan C. Santos, Postdoctoral Fellow Office: LSB 4136 Phone: 801-422-4398 e-mail: infraguttatus@gmail.com Office Hours: by appointment |
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Term |
Winter (2015) |
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Times |
T-Th,
2:00 – 2:50 p.m. |
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Room |
2142 LSB (2nd floor LSB) |
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Credits |
2 credits |
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Prerequisites |
A graduate-level course in ÔPhylogenetic SystematicsÕ and basic knowledge of R scripting (recommended) |
Course Description
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This course is a Ôhands onÕ practice and
application of phylogenetic comparative methods. For this purpose, I will
introduce different statistical and quantitative methods for analyzing
character evolution and ecological and evolutionary processes along
phylogenetic trees. We will use different R packages and other freely
available software that allow us to analyze and retrieve data from online
repositories, but students are also encouraged to use their own research data
for this purpose. The statistical and theoretical foundations of techniques
will be discussed, but the emphasis of this course is on the analysis,
visualization and implementation of the current comparative methodologies.
The main topics include: (1) brief introduction to R scripting and
environment, (2) data retrieval from online databases for the construction of
phylogenetic trees, (3) sequence alignment and phylogenetic inference, (4)
tree manipulation and visualization, (5) ancestral state reconstruction, (6)
diversification analyses and trait evolution inferences, (7) tree and data
simulations, and (8) multivariate comparative methods. The list of R packages
and software that we will review and implement are provided below. Students
will conduct a course project based on their own datasets and prepare a final
report and presentation. |
Course Format
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The course will consist of lab sessions during each class with an
introduction of the methodologies and a brief discussion of relevant key
literature. During the first nine classes, students will develop and present
a work plan for their course projects using their own data. Subsequent
meetings will cover additional topics with the opportunity for the students
to request practice of specific methodologies in support of their projects.
For suggestions about methods, you are encouraged to visit the CRAN Task
View: Phylogenetics, Especially Comparative Methods
(http://cran.r-project.org/web/views/Phylogenetics.html). The final evaluation will be student-led presentations of
their projects and a written report in manuscript format.
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*2142 LSB
(computer room) is equipped with PC computers, but most of software runs at
its best in MAC OS systems. Students are encouraged to bring their own
computer to the lab. |
Prerequisites
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Students should have had at least one upper-level course in Evolutionary Biology or ÔPhylogenetic SystematicsÕ. It is also recommended some basic univariate statistics methods and knowledge of statistical inference, but these latter components are not a requirement. The instructorÕs consent is required after discussing possible course projects, as students need to have a suitable dataset for their final projects. |
Textbooks
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There are no required textbooks and all course material will be
provided as pdf files. Students are encouraged to
read the manuals of each software or R package. However, the following
reference may be useful for the course:
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Emmanuel Paradis (2012) Analysis of Phylogenetics and Evolution with R. Second Edition.
Springer. ISBN 978-1-4614-1742-2*
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*This book is available to download at the Harold B. Lee Library |
Grading
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Total Grade (%) |
Due Date |
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Participation (showing up in class, asking
questions, participating in the discussions) |
20 |
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Project Proposal (5-10 minute presentation) |
10 |
Feb-5 |
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Final Presentation (10-15 minute
presentation) |
20 |
Apr 9
and Apr 14 |
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Final Project Report |
50 |
Day of
presentation |
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Course Topics and Schedule |
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Date |
Topic |
Software and R packages |
Presentation |
Data |
References |
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Jan 6 |
Introduction to R and comparative methods |
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Jan 8 |
Introduction to R basic functions |
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Jan 13 |
Getting sequences from GenBank (manually)
and BLAST |
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Jan 15 |
Getting sequences from GenBank into R |
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Jan 20 |
Alignment: Simultaneous alignment
and tree estimation |
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Jan 22 |
Alignment visualization and
manipulation |
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Jan 27 |
Statistical estimation of models of sequence evolution |
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Jan 29 |
Implementation of models of
sequence evolution and phylogenetic inference |
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Feb 3 |
Chronogram estimation: Penalized Likelihood Approach |
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Feb 5 |
Project proposal
presentation |
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-- |
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Feb 10 |
Chronogram estimation: BEAST |
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Feb 12
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Tree visualization, plotting |
R_commands |
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Feb 17 |
NO CLASS | ||||
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Feb 19 |
Data retrieval, supertrees and data concordance |
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Feb 24 |
Ancestral
state reconstruction (discrete)
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'ape’
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data1, data2, data3, data4
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Feb 26 |
Ancestral state
reconstruction (continuous)
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'ape’
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data1, data2, data3, data4
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Mar 3 |
Tree simulations
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'ape’
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Mar 5 |
Ancestral state
reconstruction (Threshold models)
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data1, data2, data3, data4,
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Mar 10 |
Diversification
analysis: BiSSE (MLE) based models
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Mar 12 |
Diversification
analysis: BiSSE (Bayesian) based models
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Mar 17 |
Trait
evolution: Correlation analyses (discrete traits)
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'phytools', 'corHMM', |
data1, data2, data3, data4, R_commands
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Mar 19 |
Trait
evolution: Correlation analyses (continuous traits)
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‘caper’
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Mar 24 |
Trait
evolution: Correlation analyses (discrete with continuous traits)
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‘caper’,
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data1, data2
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Mar 26 |
Open Class: Project Preparation in class |
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Mar 31 |
Taxonomy, geographic records, and multivariate methods (e.g., PPCA) |
'ape’
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Apr 2 |
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Apr 7 |
Cluster fun:
Running programs and jobs
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Apr 9 |
Student presentations of
final project |
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Apr 14 |
Student presentations of
final project |
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Printable version of this
syllabus: PDF