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.      ADVANCED PYTHON FOR BIOLOGISTS (February 2017) #APYB
http://www.prstatistics.com/course/advanced-python-biologists-apyb01/

2. STABLE ISOTOPE MIXING MODELS USING SIAR, SIBER AND MIXSIAR USING R (February 2017) #SIMM
http://www.prstatistics.com/course/stable-isotope-mixing-models-using-r-simm03/

3.      NETWORK ANAYLSIS FOR ECOLOGISTS USING R (March 2017) #NTWA
http://www.prstatistics.com/course/network-analysis-ecologists-ntwa01/

4. ADVANCES IN MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (April 2017) #MVSP
http://www.prstatistics.com/course/advances-in-spatial-analysis-of-multivariate-ecological-data-theory-and-practice-mvsp02/

5.      ADVANCING IN STATISTICAL MODELLING USING R (April 2017) #ADVR
http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr06/

6. CODING, DATA MANAGEMENT AND SHINY APPLICATIONS USING RSTUDIO FOR EVOLUTIONARY BIOLOGISTS AND ECOLOGISTS (May 2017) #CDSR
http://www.prstatistics.com/course/coding-data-management-and-shiny-applications-using-rstudio-for-evolutionary-biologists-and-ecologists-cdsr01/

7.      GEOMETRIC MORPHOMETRICS USING R (June 2017) #GMMR
http://www.prstatistics.com/course/geometric-morphometrics-using-r-gmmr01/

8.      MULTIVARIATE ANALYSIS OF SPATIAL ECOLOGICAL DATA (June 2017) #MASE
http://www.prstatistics.com/course/multivariate-analysis-of-spatial-ecological-data-using-r-mase01/

9.      TIME SERIES MODELS FOR ECOLOGISTS USING R (JUNE 2017 (#TSME)

10.     BIOINFORMATICS FOR GENETICISTS AND BIOLOGISTS (July 2017) #BIGB
http://www.prstatistics.com/course/bioinformatics-for-geneticists-and-biologists-bigb02/

11.     SPATIAL ANALYSIS OF ECOLOGICAL DATA USING R (August 2017) #SPAE
http://www.prstatistics.com/course/spatial-analysis-ecological-data-using-r-spae05/

12.     ECOLOGICAL NICHE MODELLING (October 2017) #ENMR
http://www.prstatistics.com/course/ecological-niche-modelling-using-r-enmr01/

13.     INTRODUCTION TO BIOINFORMATICS USING LINUX (October 2017) #IBUL
http://www.prstatistics.com/course/introduction-to-bioinformatics-using-linux-ibul02/

14.     GENETIC DATA ANALYSIS USING R (October 2017 TBC) #GDAR

15. STRUCTURAL EQUATION MODELLING FOR ECOLOGISTS AND EVOLUTIONARY BIOLOGISTS (October 2017) #SEMR

16. LANDSCAPE (POPULATION) GENETIC DATA ANALYSIS USING R (November 2017 TBC) #LNDG
http://www.prstatistics.com/course/landscape-genetic-data-analysis-using-r-lndg02/

17. APPLIED BAYESIAN MODELLING FOR ECOLOGISTS AND EPIDEMIOLOGISTS (November 2017) #ABME
http://www.prstatistics.com/course/applied-bayesian-modelling-ecologists-epidemiologists-abme03/

18.     INTRODUCTION TO METHODS FOR REMOTE SENSING (November 2017) #IRMS

19.     INTRODUCTION TO PYTHON FOR BIOLOGISTS (November 2017) #IPYB
http://www.prstatistics.com/course/introduction-to-python-for-biologists-ipyb04/

20. DATA VISUALISATION AND MANIPULATION USING PYTHON (December 2017) #DVMP
http://www.prstatistics.com/course/data-visualisation-and-manipulation-using-python-dvmp01/

21.     ADVANCING IN STATISTICAL MODELLING USING R (December 2017) #ADVR
http://www.prstatistics.com/course/advancing-statistical-modelling-using-r-advr07/

22.     INTRODUCTION TO BAYESIAN HIERARCHICAL MODELLING (January 2018) #IBHM
http://www.prstatistics.com/course/introduction-to-bayesian-hierarchical-modelling-using-r-ibhm02/

23.     ANIMAL MOVEMENT ECOLOGY February 2018) #ANME

24.     AQUATIC TELEMENTRY DATA ANALYSIS USIR R (February 2018) #ATDAR

25.     PHYLOGENETIC DATA ANALYSIS USING R (TBC) #PHYL


Oliver Hooker PhD.
PR statistics

3/1
128 Brunswick Street
Glasgow
G1 1TF

+44 (0) 7966500340

www.prstatistics.com
www.prstatistics.com/organiser/oliver-hooker/

--
Oliver Hooker PhD.
PR statistics

3/1
128 Brunswick Street
Glasgow
G1 1TF

+44 (0) 7966500340

www.prstatistics.com
www.prstatistics.com/organiser/oliver-hooker/

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