A quality control portal for sequencing data deposited at the European genome-phenome archive.

Since its launch in 2008, the European Genome-Phenome Archive (EGA) has been leading the archiving and distribution of human identifiable genomic data. In this regard, one of the community concerns is the potential usability of the stored data, as of now, data submitters are not mandated to perform any quality control (QC) before uploading their data and associated metadata information. Here, we present a new File QC Portal developed at EGA, along with QC reports performed and created for 1 694 442 files [Fastq, sequence alignment map (SAM)/binary alignment map (BAM)/CRAM and variant call format (VCF)] submitted at EGA.

Beacon v2 and Beacon networks: A "lingua franca" for federated data discovery in biomedical genomics, and beyond.

Beacon is a basic data discovery protocol issued by the Global Alliance for Genomics and Health (GA4GH). The main goal addressed by version 1 of the Beacon protocol was to test the feasibility of broadly sharing human genomic data, through providing simple "yes" or "no" responses to queries about the presence of a given variant in datasets hosted by Beacon providers. The popularity of this concept has fostered the design of a version 2, that better serves real-world requirements and addresses the needs of clinical genomics research and healthcare, as assessed by several contributing projects and organizations.

The European Genome-phenome Archive in 2021.

The European Genome-phenome Archive (EGA - https://ega-archive.org/) is a resource for long term secure archiving of all types of potentially identifiable genetic, phenotypic, and clinical data resulting from biomedical research projects. Its mission is to foster hosted data reuse, enable reproducibility, and accelerate biomedical and translational research in line with the FAIR principles.

Every which way? On predicting tumor evolution using cancer progression models.

Successful prediction of the likely paths of tumor progression is valuable for diagnostic, prognostic, and treatment purposes. Cancer progression models (CPMs) use cross-sectional samples to identify restrictions in the order of accumulation of driver mutations and thus CPMs encode the paths of tumor progression. Here we analyze the performance of four CPMs to examine whether they can be used to predict the true distribution of paths of tumor progression and to estimate evolutionary unpredictability.

Cellular stress responses in hepatitis C virus infection: Mastering a two-edged sword.

Hepatitis C virus (HCV) infection affects chronically more than 150 million humans worldwide. Chronic HCV infection causes severe liver disease and hepatocellular carcinoma. While immune response-mediated events are major players in HCV pathogenesis, the impact that viral replication has on cellular homeostasis is increasingly recognized as a necessary contributor to pathological manifestations of HCV infection such as steatosis, insulin-resistance or liver cancer.

HCV-specific immune responses induced by CIGB-230 in combination with IFN-α plus ribavirin.

Aim: To analyze hepatitis C virus (HCV)-specific immune responses in chronically infected patients under triple therapy with interferon-α (IFN-α) plus ribavirin and CIGB-230.

Methods: CIGB-230 was administered in different schedules with respect to IFN-α plus ribavirin therapy. Paired serum and peripheral blood mononuclear cells (PBMC) samples from baseline and end of treatment were analyzed.