Course Announcement

NOTE: please apply as soon as possible, the period for applications is exceptionally short due to operational reasons

Automated and reproducible analysis of NGS data

   Deadline for applications: October 8th 2013
   Notification of acceptance dates: October 15th 2013
   Course date: October 21st - October 24th 2013

Course Description:
Next generation sequencing (NGS) technologies for DNA have resulted in a yet bigger deluge of data. Researchers are learning that analysing such data sets is becoming the bottleneck in their work. In many cases, several steps in these analyses are fairly generic (e.g. quality control filtering, alignment to reference sequences, typing) so that off-the-shelf pipelines can be applied. In other cases, novel research approaches require development of new analysis pipelines. Either way, all analysis steps should be repeatable and any changes made to the data (e.g. renaming, annotation, alignment) should be recorded so that the provenance of the results is clear and inferences are reproducible. In this brief workshop we will establish several best practices of reproducibility and provenance recording in the (comparative) analysis of data obtained by NGS. In doing so we will encounter the commonly used technologies that enable these best practices by working through use cases that illustrate the underlying principles. Building on the basis of workflow development, we will further illustrate how custom-built workflows can be manipulated using graphical platforms (e.g. Galaxy, Taverna, etc.).

Best practices

    Standardized project organization
    Projects 'runnable' without user intervention
    No loss of data, metadata, parameters or source code through versioning
    Sharing of scripts and workflows


    Next generation sequencing platforms
    File formats (e.g. FASTQ, SAM/BAM, GFF3)
    Command-line executables, command line scripting and batching
    High-level programming with domain-specific toolkits
    Revision control systems
    Workflow environments (both visual and command line)

Use cases

    Phylogenetic placement of metagenomic data
    Typing of pathogens
    Comparative analysis of multicellular genomic data
    Post-assembly: handling richly annotated genomes

More information, including application instructions, available at

Thank you
Pedro Fernandes
GTPB coordinator

Pedro Fernandes
Instituto Gulbenkian de Ciência
Apartado 14
2781-901 OEIRAS
Tel +351 21 4407912

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