Bi7527 Data Analysis in R

Faculty of Science
Spring 2011
Extent and Intensity
2/0/0. 2 credit(s) (fasci plus compl plus > 4). Type of Completion: zk (examination).
Mgr. Eva Budinská, Ph.D. (lecturer)
Guaranteed by
prof. RNDr. Ladislav Dušek, Ph.D.
RECETOX - Faculty of Science
Contact Person: Mgr. Eva Budinská, Ph.D.
Prerequisites (in Czech)
Bi5040 Biostatistics - basic course
Bi5040 Biostatistika – základní kurz, Bi8600 Vícerozměrné statistické metody, Bi8660 Analýza dat na PC II. Pro absolvování kurzu je nutná základní znalost používání programu R, dále znalost základních statistických metod nejméně v rozsahu předmětu Bi5040 Biostatistika-základní kurz a znalost vícerozměrných statistických metod v rozsahu předmětu Bi8600 Vícerozměrné statistické metody.
Course Enrolment Limitations
The course is offered to students of any study field.
The capacity limit for the course is 30 student(s).
Current registration and enrolment status: enrolled: 0/30, only registered: 0/30, only registered with preference (fields directly associated with the programme): 0/30
Course objectives
At the end of the course students will be able to pre-process and treat the large-scale high-dimensional data in R, know and be able to use the most common R functions and packages for multivariate analysis and master the graphical representation of the results, both at the publication level.
  • 1. Short introduction to R - installation, libraries, basic data types and structures, creating functions
  • 2. Data formats, data upload
  • 3. Data pre-processing, transformations
  • a) basic pre-processing and data transformation
  • b) Data quality control (smoothing, regression)
  • 4. Basic statistical methods in R
  • a) hypothesis testing
  • b) multiple hypothesis testing correction
  • 5. Multivariate statistical methods in R - packages
  • 6. Bioconductor – the open source and open development software project for the analysis and comprehension of genomic data
  • 7. R graphics
  • a) Principles of creating and saving graphs in R
  • b) simple graphics – scatterplot, histogram, boxplot...
  • c) graph modification – color and size adjustment, graph annotation, multiple graphs display
  • d) advanced graphics – heatmaps, composed graphs, functions grid and lattice
  • GENTLEMAN, Robert. R programming for bioinformatics. Boca Raton: CRC Press, 2009. xii, 314. ISBN 9781420063677. info
  • MURRELL, Paul. R graphics. Boca Raton, Fla.: Chapman & Hall/CRC, 2006. xix, 301. ISBN 158488486X. info
  • Bioinformatics and computational biology solutions using R and bioconductor. Edited by Robert Gentleman. New York: Springer, 2005. xix, 473. ISBN 0387251464. info
Teaching methods
Education is performed in a block of simultaenous lectures in presentation and exercises. The basics and theory are explained in presentation and the students apply the acquired knowledge in R simultaneously after each topic in the presentation. The number of students in the course must not exceed the number of available computers (student notebooks included). Students are motivated to propose and discuss their own algorithmic solutions to particular problems.
Assessment methods
The final exam is practical - students have to analyse the example data together with the description and reasoning of particular steps of the analysis and applied functions.
Language of instruction
Further comments (probably available only in Czech)
The course is taught annually.
The course is taught: in blocks.
General note: Předmět je vyučován blokově.
Information on course enrolment limitations: Doporučení absolvovat Bi8600, DSMBz01, Bi3060
The course is also listed under the following terms Spring 2011 - only for the accreditation, Autumn 2009, Spring 2012, spring 2012 - acreditation, Spring 2013, Spring 2014, Spring 2015, Spring 2016, Spring 2017, spring 2018, Spring 2019, Spring 2020.
  • Enrolment Statistics (Spring 2011, recent)
  • Permalink: