The Carpentries training program aims to improve data literacy and reproducible science. IMCI sponsors the University of Idaho as a member in the organization.

Four workshops will be offered this spring for upper-level undergraduate students, new graduate students and anyone else interested in good-practices in data management and analysis.

STUDENTS wishing to take the workshops for credit need to register via the UI course schedule for any combination of BCB 503 01, BCB 503 02, BCB 503 03 and/or BCB 503 04. Each workshop is 1 credit each.

NON-STUDENTS and those who do not want academic credit must also register to attend. Attendance is free. Space is limited. A limited number of in person seats will be offered. An online option will also be available.

Genomics (1 cr)


Instructors: Lukas Grossfurthner (I), James Van Leuven (I), Clint Elg (I)

February 15-24, T/Th, 2-5 pm

Course Title: Data Carpentries: Data Wrangling and Processing for Genomics

Course Description: Data Carpentries aims to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. This hands-on workshop will cover basic concepts and tools, including best practices for organization of bioinformatics projects and data, use of command-line utilities, use of command-line tools (shell and R) to analyze sequence quality and perform variant calling, connecting to and using cloud (AWS) computing, and visualizing genomic data. The course is aimed at graduate students and other researchers, but is open to all. While the course is designed for learners that have no prior experience with the tools covered in the workshop, some familiarity with biological concepts (DNA, mutation, population variation). Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. For more information see https://imci.uidaho.edu/data-carpentries-training/.

Schedule:

Feb 15: Introductions, Review file manipulations in shell, setting up AWS, installing command-line programs

Feb 17: Overview of sequencing, data formats, input/output/synopsis of each command-line program

Feb 22: De novo assembly, Mapping to reference sequences

Feb 24: Graphing output in R, understanding data quality, Putting it all together with shell scripts

WTF (what they forgot) R workshop (1 cr)


Instructors: Julia Piaskowski (I), Breanna Sipley (I), Yesol Sapozhnikov (I)

Course Title: Intermediate R: what they forgot to teach you about R

March 1-10, T/Th, 2-5 pm

Course Description: The WTF workshop is a hands-on learning experience. We will focus on building project-oriented workflows that address the most common sources of friction in data analysis. The target learner:

  • Has a moderate amount of R and RStudio experience.
  • Is largely self-taught.
  • Suspects that they have drifted into some idiosyncratic habits that may slow them down or make their work products more brittle.
  • Is interested in (re)designing their R lifestyle, to be more effective and more self-sufficient.

Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. For more information see https://imci.uidaho.edu/data-carpentries-training/.

Schedule:

March 1: Introductions

March 3: 

March 8:

March 10:

Data Visualization in R and Python (1 cr)


Instructors: Boyu Zhang (I), Chava Castaneda (I), Akorede SeriBreanna Sipley (I), Chava Castaneda (I), Travis Seaborn (I), Akorede Seriki (I), Janet Williams (I/H), Kristen Martinet (H) 

March 29 – April 7, T/Th, 2-5 pm

Course Title: Data Carpentries: Data Visualization in R and Python

Course Description: Data Carpentries aims to teach researchers basic concepts, skills, and tools for working with data so that they can get more done in less time, and with less pain. This hands-on workshop will cover the use of the R and python programming languages for visualizing complex data and making pretty figures. The course is aimed at graduate students and other researchers, but is open to all and is designed for learners that have no prior experience in programming. However, some experience in R or Python may be useful. Participants must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. For more information see https://imci.uidaho.edu/data-carpentries-training/.

Schedule:

March 29: Introductions, graphical theory, programming languages for plotting

March 31: R or Python

April 5: R or Python

April 7: R or Python

Advanced Geospatial Analysis (1 cr)


Instructors: Erich Seamon (I),Li Huang (I), Travis Seaborn (I)

April 26 – May 5, T/Th, 2-5 pm

Course Title: Data Carpentry: Adv. Geospatial Analysis

Course Description: This hands-on workshop will focus on managing and understanding spatial data formats, understanding coordinate reference systems, and working with raster and vector data in R for analysis and visualization. The course is aimed at graduate students and other researchers, but is open to all. Participants will be encouraged to help one another and to apply what they have learned to their own research problems. An introductory knowledge of Python is suggested.

Attendees must bring a laptop with a Mac, Linux, or Windows operating system (not a tablet, Chromebook, etc.) that they have administrative privileges on. For more information see https://imci.uidaho.edu/data-carpentries-training/.

Schedule:

April 26: Introductions,

April 28:

May 3:

May 5: