Biology subjects

Paolo Ribeca

Publications and source records attributed to Paolo Ribeca.

3 recordsLinked to original sources

bioRxiv2016

ChimPipe: Accurate detection of fusion genes and transcription-induced chimeras from RNA-seq data

BackgroundChimeric transcripts are commonly defined as transcripts linking two or more different genes in the genome, and can be explained by various biological mechanisms such as genomic rearrangement, read-through or trans-splicing, but also by technical or biological artefacts. Several studies have shown their importance in cancer, cell pluripotency and motility. Many programs have recently been developed to identify chimeras from Illumina RNA-seq data (mostly fusion genes in cancer). However outputs of different programs on the same dataset can be widely inconsistent, and tend to include many false positives. Other issues relate to simulated datasets restricted to fusion genes, real datasets with limited numbers of validated cases, result inconsistencies between simulated and real datasets, and gene rather than junction level assessment.\n\nResultsHere we present ChimPipe, a modular and easy-to-use method to reliably identify chimeras from paired-end Illumina RNA-seq data. We have also produced realistic simulated datasets for three different read lengths, and enhanced two gold-standard cancer datasets by associating exact junction points to validated gene fusions. Benchmarking ChimPipe together with four other state-of-the-art tools on this data showed ChimPipe to be the top program at identifying exact junction coordinates for both kinds of datasets, and the one showing the best trade-off between sensitivity and precision. Applied to 106 ENCODE human RNA-seq datasets, ChimPipe identified 137 high confidence chimeras connecting the protein coding sequence of their parent genes. In subsequent experiments, three out of four predicted chimeras, two of which recurrently expressed in a large majority of the samples, could be validated. Cloning and sequencing of the three cases revealed several new chimeric transcript structures, 3 of which with the potential to encode a chimeric protein for which we hypothesized a new role.\n\nConclusionsChimPipe combines spanning and paired end RNA-seq reads to detect any kind of chimeras, including read-throughs, and shows an excellent trade-off between sensitivity and precision. The chimeras found by ChimPipe can be validated in-vitro with high accuracy.

Bioinformatics↗

bioRxiv2014

A Comprehensive Assessment of Somatic Mutation Calling in Cancer Genomes

The emergence of next generation DNA sequencing technology is enabling high-resolution cancer genome analysis. Large-scale projects like the International Cancer Genome Consortium (ICGC) are systematically scanning cancer genomes to identify recurrent somatic mutations. Second generation DNA sequencing, however, is still an evolving technology and procedures, both experimental and analytical, are constantly changing. Thus the research community is still defining a set of best practices for cancer genome data analysis, with no single protocol emerging to fulfil this role. Here we describe an extensive benchmark exercise to identify and resolve issues of somatic mutation calling. Whole genome sequence datasets comprising tumor-normal pairs from two different types of cancer, chronic lymphocytic leukaemia and medulloblastoma, were shared within the ICGC and submissions of somatic mutation calls were compared to verified mutations and to each other. Varying strategies to call mutations, incomplete awareness of sources of artefacts, and even lack of agreement on what constitutes an artefact or real mutation manifested in widely varying mutation call rates and somewhat low concordance among submissions. We conclude that somatic mutation calling remains an unsolved problem. However, we have identified many issues that are easy to remedy that are presented here. Our study highlights critical issues that need to be addressed before this valuable technology can be routinely used to inform clinical decision-making.\n\nAbbreviations and Definitionsaligner = mapper, these terms are used interchangeably

Genomics↗

bioRxiv2014

A comprehensive multicenter comparison of whole genome sequencing pipelines using a uniform tumor-normal sample pair

As next-generation sequencing becomes a clinical tool, a full understanding of the variables affecting sequencing analysis output is required. Through the International Cancer Genome Consortium (ICGC), we compared sequencing pipelines at five independent centers (CNAG, DKFZ, OICR, RIKEN and WTSI) using a single tumor-blood DNA pair. Analyses by each center and with one standardized algorithm revealed significant discrepancies. Although most pipelines performed well for coding mutations, library preparation methods and sequencing coverage metrics clearly influenced downstream results. PCR-free methods showed reduced GC-bias and more even coverage. Increasing sequencing depth to [~]100x (two- to three-fold higher than current standards) showed a benefit, as long as the tumor:control coverage ratio remained balanced. To become part of routine clinical care, high-throughput sequencing must be globally compatible and comparable. This benchmarking exercise has highlighted several fundamental parameters to consider in this regard, which will allow for better optimization and planning of both basic and translational studies.

Genomics↗