Emblem of the Republic of Poland Uniwersytet Jagielloński
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Practical computing for biologists – a gentle introduction
Educational subject description sheet

Basic information

Field of study
Biology
Speciality
-
Organizational unit
Faculty of Biology
Study level
second cycle
Study form
full-time degree programme
Education profile
General academic
Mandatory
elective
Education cycle
2024/25
Subject code
UJ.WBlBIOS.250.15052.24
Lecture languages
english
Subject related to scientific research
Yes
Disciplines
Biological sciences
ISCED classification
0511 Biology
USOS code
Subject coordinator
Wiesław Babik, Piotr Zieliński
Lecturer
Wiesław Babik, Piotr Zieliński
Periods
Semester 1, Semester 3
Examination
graded credit
Activities and hours
Classes: 45
Number of ECTS points
5.0

Goals

C1 To teach the students how to automate handling and processing various forms of data using standard Linux/Unix command-line tools and the R programming language

Subject's learning outcomes

Code Outcomes in terms of Effects Examination methods
Knowledge – Student knows and understands:
W1 student knows how to format and organize data within data files and files into folders BIO_K2_W09, BIO_K2_W10 credit with grade
W2 student understands the format and structure of text files BIO_K2_W09, BIO_K2_W10 credit with grade
W3 student knows the Linux shell commands and command-line utilities used to automate data processing and analysis BIO_K2_W09, BIO_K2_W10 credit with grade
W4 student knows the basic commands of R language, as well as the role of R packages in data analysis BIO_K2_W09 credit with grade
Skills – Student can:
U1 connect to a remote Linux machine and work in the Linux shell environment BIO_K2_U06 credit with grade
U2 use Nano text editor BIO_K2_U06 credit with grade
U3 automate routine tasks in data handling and analysis using the Linux shell and command-line utilities BIO_K2_U01, BIO_K2_U06 credit with grade
U4 use R and R studio to visualize, summarise, reformat and filter data BIO_K2_U01, BIO_K2_U06 credit with grade
Social competences – Student is ready for:
K1 understands the central role of text files in data exchange and analysis BIO_K2_K02, BIO_K2_K08 credit with grade
K2 the understands and appreciates the advantages of using command-line tools in the analysis of biological data BIO_K2_K02, BIO_K2_K08 credit with grade
K3 appreciates the benefits of scripts as a permanent record of the data analysis critical for reproducible science BIO_K2_K02, BIO_K2_K08 credit with grade

Calculation of ECTS points

Activity form Activity hours*
Classes 45
preparation for exercises 30
preparation for final test 25
computer tasks solving 25
Student workload
Hours
125
ECTS
5.0

* hour means 45 minutes

Study content

No. Course content Subject's learning outcomes
1.

  • Organising data in a spreadsheet or spreadsheet-like format, relations between tables

  • Text files, text editors and regular expressions

  • Connecting to a remote Linux machine, 

  • Moving around in the Linux system

  • Linux command-line utilities and pipelines

  • Automation with shell scripts

  • R and RStudio 

  • Data in R

  • Subsetting and working with data frames

  • Tidyverse

  • Plotting 

  • Practical examples of handling biological data (miniprojects)

 W1, W2, W3, W4, U1, U2, U3, U4, K1, K2, K3

Course advanced

Teaching methods :

discussion, practicals, consultation

Activities Examination methods Credit conditions
Classes credit with grade to pass, the student has to obtain > 50% of the maximum score at the practical test

Entry requirements

none

Literature

Obligatory
  1. Instrukcje do ćwiczeń przygotowane przez prowadzących / Manuals prepared by the instructors
Optional
  1. Wickham, H., & Grolemund, G. (2016). R for data science: import, tidy, transform, visualize, and model data. O'Reilly Media, Inc.
  2. Shotts, W. (2019). The Linux command line: a complete introduction. No Starch Press.