About the


Life sciences have become an increasingly quantitative discipline. Research in life sciences rely on high-throughput methods for collecting genetic information, collectively named the next-generation sequencing. These methods generate vast quantities of genomic data and require a specific set of skills to analyse and interpret them.

This series of courses aims at closing the gap between bench scientists and data they experimentally generate. They provide an overview of statistical methods and computational environment to successfully manipulate, analyse and visualize next-generation sequencing data.

The courses are limited to 15 participants and will be filled on a first-come first-serve basis, so we suggest you to register early and secure your place at one or both courses. Participants who register for both courses get a discounted price: -10% .

Statistics and R

will provide participants with the basic statistical methods used in life sciences and familiarize them with the data analysis framework based around the R statistical package

  • R statistical framework
  • Rstudio environment
  • Packages, modules
  • Reading and manipulating datasets
  • Exploratory and descriptive statistics
  • Statistical distributions and testing
  • Plotting

2 days

Next generation sequencing analysis

will provide participants with the hands-on approach to analysing high-throughput genomic experiments, from the instrument output (DNA or RNA sequence) to relevant biological and biomedical knowledge

  • Experimental design for NGS
  • Instrument output formats (DNAseq, RNAseq, ChIPseq)
  • Reference mapping
  • Visualization of genomic tracks
  • Expression quantification and analysis (RNASeq)
  • Variant detection (DNAseq)

3 days

Meet the team


Guest lecturer:

Rok Količ (Kemomed)

Illumina NGS software platform (Base space and variant calling)

  • RStudio, getting help, packages
  • Mathematical and logical operators
  • Basic data types (vector, list, factor, matrix, etc.)
  • variable assignment
  • Generating sequences (rep, seq)
  • Vector/matrix arithmetic
  • NA and NA arithmetic/logic
  • Reading and writing data

  • Summary functions
  • Conditions - if, ifelse
  • Loops - for, while
  • apply functions
  • Functions, writing functions

  • Displaying univariate and multivariate data
  • Changing parameter
  • Histograms, boxplots

  • String functions (substr, strsplit, paste, nchar)
  • Regex and regex functions(grep, grepl, sub, gsub)
  • Manipulating data.frames - merge, match, duplicated

  • Random numbers and distributions (sample, r*, q*, p*, d* functions)
  • Examining distributions - graphical and numerical summaries

  • t-test
  • chi-square test
  • Shapiro-Wilk test
  • 30 minutes breake
  • Linear regression

  • Introduction to next generation sequencing
  • RNA-seq, whole exome sequencing
  • Read quality report, trimming, filtering
  • Read mapping

  • Biostrings - general sequence analysis environment
  • String matching
  • Random sequence generation
  • alphabetFrequency, reverseComplement, translate
  • creating strings
  • reading FASTA files
  • BSGenome package
  • Getting data for different genomes
  • IRanges, GenomicRanges
  • Creating ranges
  • Interval functions (overlap, reduce, disjoin, intersect)
  • Overview of different Bioconductor packages

  • Expression estimation
  • Normalization strategies
  • Differential expression analysis

  • Variant calling
  • ChIP-Seq
  • Peak calling
  • Motif finding
  • Differential binding

  • Data visualization with IGV
  • Data preparation for Genome Browser

    Illumina NGS software platform (Base space and variant calling)




Borongajska cesta 83h
10000, Zagreb.
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