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The Huber Group at EBI

The Huber Group at EBI. 10 September 2008. Goals. “To develop mathematical, statistical and computational methods for the analysis of biologically or technologically novel experiments, in order to understand regulatory and genetic interaction networks.”. Collaboration model.

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The Huber Group at EBI

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  1. The Huber Group at EBI 10 September 2008

  2. Goals “To develop mathematical, statistical and computational methods for the analysis of biologically or technologically novel experiments, in order to understand regulatory and genetic interaction networks.”

  3. Collaboration model • Typically, projects involve one-on-one collaborations with experimentalists and include all aspects of… • Experiment design, quality control and normalization • Statistical analysis • Biological interpretation • Bioinformatic integration and comparison with other data • Identification and design of follow-up experiments • Required skills: • Solid maths • Statistics • Programming • Speed and efficiency • Communication • Perfection • Perfectionism

  4. Genome-wide morphology screen • Collaboration with FlorianFuchs & Michael Boutros, DKFZ, Heidelberg. • HeLa cells, reverse transfected with DharmaconsiRNA library (21,500 pools, 4 distinct siRNAs each). • After 48 hours stain three channels: • Actin (TRITC)‏ • Tubulin (Alexa 488)‏ • DNA (Hoechst)‏ • BD Pathway, images at 4 sites per well, two replicate scans: 172,000 x 1 megapixels x 12 bit.

  5. Workflow • Voronoi segmentation (on image manifold) of nuclei and cells. • Extraction of 30-50 quantitative features per cell • Clustering and classification of millions of per-cell phenotypes by machine learning

  6. Workflow • Voronoi segmentation (on image manifold) of nuclei and cells. • Extraction of 30-50 quantitative features per cell • Clustering and classification of millions of per-cell phenotypes by machine learning • Cell phenotype profile for each of 21,500 siRNA-pools • Identification of per-gene phenotypes by classification and statistical testing

  7. High-density tiling arrays and S. cerevisiae • Collaborations with Lars Steinmetz’s lab, EMBL Heidelberg. • Custom Affymetrix tiling microarray: • 6.5 million 25-mer probes. • Tiles non-repetitive portion of S96 genome at 4-base resolution. • 4% of probes match variant YJM789 sequence instead. • S96-specific probes permit unbiased analysis of transcription.

  8. Genotyping, via genomic DNA hybridization

  9. Genotypes, recombination events, and recombination fraction

  10. Allele-specific transcription Expression level estimation: • Background correction using DNA hybridizations • Bilinear model with heteroscedastic of error term • Constrained least squares

  11. Bioconductor • Good scientific software is like good research: it is… • Reproducible. • Openly accessible. • Built upon past work. • A building block for future work. • Bioconductor • An open source and open development software project for the analysis of biomedical and genomic data. • Initiated in 2001 by Robert Gentleman, FHCRC, Seattle. • ~10 core developers, ~100 contributors, ~180 packages, thousands of users.

  12. Other ongoing projects • Genome-wide RNAi screens and genetic interaction networks: • cellHTS2 • Synthetic genetic interactions • Dynamical modeling of cell populations. • Software tools for microarray quality assessment. • Hemizygosityproject. • Massively parallel sequencing for ChIP and transcript quantification.

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