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Bioinformatics
Core Facility
Figure 1. Duplication rate
analysis of RNA-seq data.
Highly expressed genes have
high duplication rates, which
dominate the overall duplication
rate of a dataset. New
quality control tools allow this
effect to be distinguished from
PCR artefacts which might
have been caused by a low
amount of input material.
People: Eugen Eirich, Emil Karaulanov,
Holger Klein, Nastasja Kreim, Joern Toedling
Core Facility Overview
The Bioinformatics Core Facility provides different levels of advanced
data analysis tools and support to IMB scientists; this support ranges
from experimental design to data evaluation. The facility is committed
to finding and providing optimal solutions for bioinformatics issues
that arise in the course of research projects. The rapidly changing landscape
of biomedical research and the ever increasing flow of highthroughput
datasets necessitate dedicated and flexible bioinformatic
support for the many projects at IMB. The facility enables researchers
to analyse experimental data themselves by providing access to stateof-the-art
software tools with workflows for standard analyses that
can be utilized and adapted to specific problems. Additionally, the
facility offers long-term support and analytical expertise for individual
research projects on a collaborative basis.
In 2012 the facility extended its hardware infrastructure with a file
server of 140TB raw capacity. This is mainly used for next-generationsequencing
datasets.
Selected Publications
Chen CJ, Servant N, Toedling J, Sarazin A, Marchais A, Berthet ED, Cognat V,
Colot V, Voinnet O, Heard E, Ciaudo C, Barillot E (2012). ncPRO-seq: a tool for annotation
and profiling of ncRNAs in sRNA-seq data. Bioinformatics, 28, 3147-3149.
Stumm M, Entezami M, Trunk N, Beck M, Löcherbach J, Wegner RD, Hagen A,
Becker R, Hofmann W (2012). Noninvasive prenatal detection of chromosomal
aneuploidies using different next generation sequencing strategies and algorithms.
Prenatal Diagnosis, 32, 569-577.
Toedling J, Servant N, Ciaudo C, Farinelli L, Voinnet O, Heard E, and Barillot E
(2012). Deep-Sequencing Protocols Influence the Results Obtained in Small-RNA
Sequencing. PLoS ONE, 7, e32724.
In 2012 the Bioinformatics Core Facility analysed datasets in several
in-house collaborations. Data analysed included that from ChIP-seq
(histone modifications and transcription factors, time series), strandspecific
and agnostic RNA-seq (differential expression and isoform
usage, time-series), MBD-seq, Bisulfite-seq, microarray and proteomics
experiments. In the course of the analyses the facility extended its standard
pipelines and engaged in the development of new quality control
tools for the assessment of read duplication rates in RNA-seq. Members
of the facility engaged in consultations regarding experimental
design and data interpretation as well as user training and education
through the provision of the following lectures and practical courses:
• International PhD Programme Lectures: Genomics, ChIP-seq,
RNA-seq, methlylomics
• International PhD Programme Practical Courses: Galaxy, Chipster,
Genomatix
• International Summer School: Bioinformatics for next-generationsequencing,
data analysis
• Other Seminars: Four lectures on various sequencing technologies
Services Offered
The Bioinformatics Core Facility provides assistance on two levels:
1. General support to the IMB user base:
• Assistance with experimental design of high-throughput assays
such as ChIP-seq, RNA-seq or Bisulfite-seq
• In-house training and tutorials on bioinformatic tools and databases
to facilitate data access and analysis
• Implementation and adaptation of open-source tools and commercial
software solutions for “omics” data interpretation
• Setup and development of analysis pipelines for sequencing,
microarray, cytometry and microscopy data
• Quality assessment and pre-processing of raw data coming from
the sequencing instruments
2. In-depth assistance for individual projects:
• Comprehensive high-throughput data analyses, interpretation
and presentation of results
• Development of custom tools to address specific bioinformatic needs
• Exploration and implementation of novel analysis methods and
pipelines
• Data mining of “omics” databases and published high-throughput
datasets
The following bioinformatic resources were installed or updated to
newer versions at IMB in 2012:
• R-Studio: new installation. A server frontend for the statistical
programming language R and BioConductor packages
• GALAXY-LIMS: new installation. A customized version of the
Galaxy laboratory information management system
• GALAXY: customization, upgrade and tighter infrastructure integration.
An open-source environment for genomics data analysis
• GENOMATIX: upgrade and tighter infrastructure integration.
Commercial software for performing standard next-generationsequencing
data mapping and analysis tasks
• CHIPSTER: upgrade. Open-source data analysis platform for
various types of microarray