First Annual RECOMB Satellite Workshop on Massively Parallel Sequencing

Third Annual
RECOMB Satellite Workshop on Computational Cancer Biology

March 26-27 2011, Vancouver, BC, Canada

Massively Parallel Sequencing (RECOMB-seq)

The revolution in DNA sequencing opened many possibilities for researchers working in the fields of genetic variation, diseases of genomic origin, and even personalized medicine. The new technologies can also be employed to discover functional landscape of the human genome as part of the ENCODE Project; such as epigenetic variation (methylation patterns and histone modification) and protein-DNA interaction. Further uses of the high-throughput sequencing technologies include transcriptome analysis, non-coding RNA discovery, gene expression profiling, rapid testing of genotype-phenotype associations, and identification of pathogens.

Recent publication of the pilot phase of the 1000 Genomes Project demonstrated the feasibility and power of massively parallel sequencing, yet also presented the challenges in analyzing the data.

We would like to invite contributions presenting new methods in algorithm development for the analysis of massively parallel sequencing data. Problems of specific interest may include, but are not limited to:

  • Read mapping
  • Discovery and genotyping of genomic variants; including SNPs, indels, and structural variants (deletions, novel insertions, inversions, duplications, translocations, mobile element insertions)
  • Local and de novo sequence assembly
  • Epigenetic variation such as methylation profiling, ChIP-seq analysis, metagenomics
  • Transcriptome analysis, RNAseq and transcriptome assembly

Computational Cancer Biology (CCB)

Cancer biology is undergoing a revolution driven by the application of high-throughput techniques such as genome and transcriptome sequencing, high resolution genotyping arrays, genome-wide epigenetic profiling, expression microarrays, miRNA profiling, and mass spectrometry to tumor samples. These techniques give rise to large collections of data that are impacting both basic cancer biology as well as clinical applications. Cancer is disease of tremendous complexity, and thus the analysis and interpretation of this data, taking a systems biology approach, demands sophisticated, specialized computational methods.

Topics of interest include, but are not limited to

  • Methods for analysis of next generation sequencing data with a specific application to cancer
  • Pathway analysis and network reconstruction with a focus on cancer biology
  • Inference of genomic rearrangements, somatic mutations, gene expression, alternative splicing from next gen sequencing data sets
  • Copy number and allelic distribution analysis from high density SNP chips
  • Epigenetic variation such as methylation profiling, methyl-seq, ChIP-seq analysis
  • Transcriptome analysis, RNAseq and transcriptome assembly
  • Data integration from multiple molecular assays
  • Integration of clinical and molecular data

RECOMB-seq and CCB will be held in parallel, with shared sessions on topics relevant to both workshops. We strongly encourage submission of abstracts / manuscripts describing computational approaches relevant to both RECOMB-seq and CCB.




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