Research & Developments
- SplicingCompass: differential splicing detection using RNA-Seq data
Alternative splicing is central for cellular processes and substantially increases transcriptome and proteome diversity. Aberrant splicing events often have pathological consequences and are associated with various diseases and cancer types.
SplicingCompass is a new method and software to predict genes that are differentially spliced between two different conditions using RNA-seq data. Our method employs geometric angles between the high dimensional vectors of exon read counts. With this, differential splicing can be detected even if the splicing events comprise of higher complexity and involve previously unknown splicing patterns. We applied our approach to two case studies including neuroblastoma tumour data with favourable and unfavourable clinical courses. We show the validity of our predictions as well as the applicability of our method in the context of patient clustering. We verified our predictions by several methods including simulated experiments
and complementary in silico analyses of the biological data itself.
- Special database for the annotation of small/nc-RNAs was created from Mirbase, Ensembl, piRNA database and RFAM. This database is used in our pipeline ncRNAannotator.
- Theoretical and practical coverage achieved by targeted exome enrichment
Exome sequencing is widely used in cancer research area due to its relatively high efficiency and low cost. These target-enrichment procedures capture the regions of interest from samples before sequencing. The selection of target regions is crucial to the performance of exome sequencing. Currently, there are different human exome enrichment platforms available provided by different companies. By comparing the target design and performance of these enrichment strategies, we found that important genes are not covered by a particular platforms, both on a theoretical basis as well as in practice. We compared the exome coverage of three platforms: Agilent's SureSelect, Illumina's Nextera Rapid Capture Exome, NimbleGen's SeqCap EZ Exome Library. We assessed the coverage of these different platforms in two ways: one is the coverage of coding mutations of genes in cancer census from COSMIC database4 (release 67), the other is the coverage of all the protein coding genes from the Ensembl database5 (release 74). On average the platforms covered about 92.51% of the coding mutations of COSMIC and 66.56% of the coding exons of Ensembl.
- ChipSeq: Peakdetector, ChipeAn, NextGene were developed for the analysis of ChipSeq data
- Ontarget, TargetCoverage and Ontarget2: coverage analysis after sub-genomic enrichment
- rnaseq analysis: Coverage and Expression analysis with the FastRNAMapper
- Contamination Analysis for unmapped reads with the Contaminator pipeline