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  1. Article ; Online: PACIFIC

    Pablo Acera Mateos / Renzo F. Balboa / Simon Easteal / Eduardo Eyras / Hardip R. Patel

    Scientific Reports, Vol 11, Iss 1, Pp 1-

    a lightweight deep-learning classifier of SARS-CoV-2 and co-infecting RNA viruses

    2021  Volume 14

    Abstract: Abstract Viral co-infections occur in COVID-19 patients, potentially impacting disease progression and severity. However, there is currently no dedicated method to identify viral co-infections in patient RNA-seq data. We developed PACIFIC, a deep- ... ...

    Abstract Abstract Viral co-infections occur in COVID-19 patients, potentially impacting disease progression and severity. However, there is currently no dedicated method to identify viral co-infections in patient RNA-seq data. We developed PACIFIC, a deep-learning algorithm that accurately detects SARS-CoV-2 and other common RNA respiratory viruses from RNA-seq data. Using in silico data, PACIFIC recovers the presence and relative concentrations of viruses with > 99% precision and recall. PACIFIC accurately detects SARS-CoV-2 and other viral infections in 63 independent in vitro cell culture and patient datasets. PACIFIC is an end-to-end tool that enables the systematic monitoring of viral infections in the current global pandemic.
    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2021-02-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  2. Article ; Online: Ribosome profiling at isoform level reveals evolutionary conserved impacts of differential splicing on the proteome

    Marina Reixachs-Solé / Jorge Ruiz-Orera / M. Mar Albà / Eduardo Eyras

    Nature Communications, Vol 11, Iss 1, Pp 1-

    2020  Volume 12

    Abstract: Genes express multiple mRNA isoforms through alternative processing. Here the authors analyze ribosome profiling data with ORQAS (ORF quantification pipeline for alternative splicing) and report that 40–50% of the expressed mRNA isoforms are translated. ...

    Abstract Genes express multiple mRNA isoforms through alternative processing. Here the authors analyze ribosome profiling data with ORQAS (ORF quantification pipeline for alternative splicing) and report that 40–50% of the expressed mRNA isoforms are translated.
    Keywords Science ; Q
    Language English
    Publishing date 2020-04-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  3. Article ; Online: Systematic benchmarking of tools for CpG methylation detection from nanopore sequencing

    Zaka Wing-Sze Yuen / Akanksha Srivastava / Runa Daniel / Dennis McNevin / Cameron Jack / Eduardo Eyras

    Nature Communications, Vol 12, Iss 1, Pp 1-

    2021  Volume 12

    Abstract: Several existing algorithms predict the methylation of DNA using Nanopore sequencing signals, but it is unclear how they compare in performance. Here, the authors benchmark the performance of several such tools, and propose METEORE, a consensus tool that ...

    Abstract Several existing algorithms predict the methylation of DNA using Nanopore sequencing signals, but it is unclear how they compare in performance. Here, the authors benchmark the performance of several such tools, and propose METEORE, a consensus tool that improves prediction accuracy.
    Keywords Science ; Q
    Language English
    Publishing date 2021-06-01T00:00:00Z
    Publisher Nature Portfolio
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  4. Article ; Online: ISOTOPE

    Juan L Trincado / Marina Reixachs-Solé / Judith Pérez-Granado / Tim Fugmann / Ferran Sanz / Jun Yokota / Eduardo Eyras

    PLoS Computational Biology, Vol 17, Iss 9, p e

    ISOform-guided prediction of epiTOPEs in cancer.

    2021  Volume 1009411

    Abstract: Immunotherapies provide effective treatments for previously untreatable tumors and identifying tumor-specific epitopes can help elucidate the molecular determinants of therapy response. Here, we describe a pipeline, ISOTOPE (ISOform-guided prediction of ... ...

    Abstract Immunotherapies provide effective treatments for previously untreatable tumors and identifying tumor-specific epitopes can help elucidate the molecular determinants of therapy response. Here, we describe a pipeline, ISOTOPE (ISOform-guided prediction of epiTOPEs In Cancer), for the comprehensive identification of tumor-specific splicing-derived epitopes. Using RNA sequencing and mass spectrometry for MHC-I associated proteins, ISOTOPE identified neoepitopes from tumor-specific splicing events that are potentially presented by MHC-I complexes. Analysis of multiple samples indicates that splicing alterations may affect the production of self-epitopes and generate more candidate neoepitopes than somatic mutations. Although there was no difference in the number of splicing-derived neoepitopes between responders and non-responders to immune therapy, higher MHC-I binding affinity was associated with a positive response. Our analyses highlight the diversity of the immunogenic impacts of tumor-specific splicing alterations and the importance of studying splicing alterations to fully characterize tumors in the context of immunotherapies. ISOTOPE is available at https://github.com/comprna/ISOTOPE.
    Keywords Biology (General) ; QH301-705.5
    Subject code 570
    Language English
    Publishing date 2021-09-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  5. Article ; Online: ReorientExpress

    Angel Ruiz-Reche / Akanksha Srivastava / Joel A. Indi / Ivan de la Rubia / Eduardo Eyras

    Genome Biology, Vol 20, Iss 1, Pp 1-

    reference-free orientation of nanopore cDNA reads with deep learning

    2019  Volume 9

    Abstract: Abstract We describe ReorientExpress, a method to perform reference-free orientation of transcriptomic long sequencing reads. ReorientExpress uses deep learning to correctly predict the orientation of the majority of reads, and in particular when trained ...

    Abstract Abstract We describe ReorientExpress, a method to perform reference-free orientation of transcriptomic long sequencing reads. ReorientExpress uses deep learning to correctly predict the orientation of the majority of reads, and in particular when trained on a closely related species or in combination with read clustering. ReorientExpress enables long-read transcriptomics in non-model organisms and samples without a genome reference without using additional technologies and is available at https://github.com/comprna/reorientexpress.
    Keywords Biology (General) ; QH301-705.5 ; Genetics ; QH426-470
    Language English
    Publishing date 2019-11-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  6. Article ; Online: The Functional Impact of Alternative Splicing in Cancer

    Héctor Climente-González / Eduard Porta-Pardo / Adam Godzik / Eduardo Eyras

    Cell Reports, Vol 20, Iss 9, Pp 2215-

    2017  Volume 2226

    Abstract: Alternative splicing changes are frequently observed in cancer and are starting to be recognized as important signatures for tumor progression and therapy. However, their functional impact and relevance to tumorigenesis remain mostly unknown. We carried ... ...

    Abstract Alternative splicing changes are frequently observed in cancer and are starting to be recognized as important signatures for tumor progression and therapy. However, their functional impact and relevance to tumorigenesis remain mostly unknown. We carried out a systematic analysis to characterize the potential functional consequences of alternative splicing changes in thousands of tumor samples. This analysis revealed that a subset of alternative splicing changes affect protein domain families that are frequently mutated in tumors and potentially disrupt protein-protein interactions in cancer-related pathways. Moreover, there was a negative correlation between the number of these alternative splicing changes in a sample and the number of somatic mutations in drivers. We propose that a subset of the alternative splicing changes observed in tumors may represent independent oncogenic processes that could be relevant to explain the functional transformations in cancer, and some of them could potentially be considered alternative splicing drivers (AS drivers).
    Keywords alternative splicing ; transcript isoforms ; isoform switch ; cancer ; protein domains ; protein-protein interactions ; networks ; cancer drivers ; TCGA ; Biology (General) ; QH301-705.5
    Subject code 570
    Language English
    Publishing date 2017-08-01T00:00:00Z
    Publisher Elsevier
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  7. Article ; Online: A Quantitative Profiling Tool for Diverse Genomic Data Types Reveals Potential Associations between Chromatin and Pre-mRNA Processing.

    Isaac Kremsky / Nicolás Bellora / Eduardo Eyras

    PLoS ONE, Vol 10, Iss 7, p e

    2015  Volume 0132448

    Abstract: High-throughput sequencing, and genome-based datasets in general, are often represented as profiles centered at reference points to study the association of protein binding and other signals to particular regulatory mechanisms. Although these profiles ... ...

    Abstract High-throughput sequencing, and genome-based datasets in general, are often represented as profiles centered at reference points to study the association of protein binding and other signals to particular regulatory mechanisms. Although these profiles often provide compelling evidence of these associations, they do not provide a quantitative assessment of the enrichment, which makes the comparison between signals and conditions difficult. In addition, a number of biases can confound profiles, but are rarely accounted for in the tools currently available. We present a novel computational method, ProfileSeq, for the quantitative assessment of biological profiles to provide an exact, nonparametric test that specific regions of the test profile have higher or lower signal densities than a control set. The method is applicable to high-throughput sequencing data (ChIP-Seq, GRO-Seq, CLIP-Seq, etc.) and to genome-based datasets (motifs, etc.). We validate ProfileSeq by recovering and providing a quantitative assessment of several results reported before in the literature using independent datasets. We show that input signal and mappability have confounding effects on the profile results, but that normalizing the signal by input reads can eliminate these biases while preserving the biological signal. Moreover, we apply ProfileSeq to ChIP-Seq data for transcription factors, as well as for motif and CLIP-Seq data for splicing factors. In all examples considered, the profiles were robust to biases in mappability of sequencing reads. Furthermore, analyses performed with ProfileSeq reveal a number of putative relationships between transcription factor binding to DNA and splicing factor binding to pre-mRNA, adding to the growing body of evidence relating chromatin and pre-mRNA processing. ProfileSeq provides a robust way to quantify genome-wide coordinate-based signal. Software and documentation are freely available for academic use at https://bitbucket.org/regulatorygenomicsupf/profileseq/.
    Keywords Medicine ; R ; Science ; Q
    Language English
    Publishing date 2015-01-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  8. Article ; Online: Predictive Models of Gene Regulation from High-Throughput Epigenomics Data

    Sonja Althammer / Amadís Pagès / Eduardo Eyras

    Comparative and Functional Genomics, Vol

    2012  Volume 2012

    Abstract: The epigenetic regulation of gene expression involves multiple factors. The synergistic or antagonistic action of these factors has suggested the existence of an epigenetic code for gene regulation. Highthroughput sequencing (HTS) provides an opportunity ...

    Abstract The epigenetic regulation of gene expression involves multiple factors. The synergistic or antagonistic action of these factors has suggested the existence of an epigenetic code for gene regulation. Highthroughput sequencing (HTS) provides an opportunity to explore this code and to build quantitative models of gene regulation based on epigenetic differences between specific cellular conditions. We describe a new computational framework that facilitates the systematic integration of HTS epigenetic data. Our method relates epigenetic signals to expression by comparing two conditions. We show its effectiveness by building a model that predicts with high accuracy significant expression differences between two cell lines, using epigenetic data from the ENCODE project. Our analyses provide evidence for a degenerate epigenetic code, which involves multiple genic regions. In particular, signal changes at the 1st exon, 1st intron, and downstream of the polyadenylation site are found to associate strongly with expression regulation. Our analyses also show a different epigenetic code for intron-less and intron-containing genes. Our work provides a general methodology to do integrative analysis of epigenetic differences between cellular conditions that can be applied to other studies, like cell differentiation or carcinogenesis.
    Keywords Science ; Q ; Biology (General) ; QH301-705.5 ; Genetics ; QH426-470
    Subject code 612
    Language English
    Publishing date 2012-01-01T00:00:00Z
    Publisher Hindawi Limited
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  9. Article ; Online: SUPPA2

    Juan L. Trincado / Juan C. Entizne / Gerald Hysenaj / Babita Singh / Miha Skalic / David J. Elliott / Eduardo Eyras

    Genome Biology, Vol 19, Iss 1, Pp 1-

    fast, accurate, and uncertainty-aware differential splicing analysis across multiple conditions

    2018  Volume 11

    Abstract: Abstract Despite the many approaches to study differential splicing from RNA-seq, many challenges remain unsolved, including computing capacity and sequencing depth requirements. Here we present SUPPA2, a new method that addresses these challenges, and ... ...

    Abstract Abstract Despite the many approaches to study differential splicing from RNA-seq, many challenges remain unsolved, including computing capacity and sequencing depth requirements. Here we present SUPPA2, a new method that addresses these challenges, and enables streamlined analysis across multiple conditions taking into account biological variability. Using experimental and simulated data, we show that SUPPA2 achieves higher accuracy compared to other methods, especially at low sequencing depth and short read length. We use SUPPA2 to identify novel Transformer2-regulated exons, novel microexons induced during differentiation of bipolar neurons, and novel intron retention events during erythroblast differentiation.
    Keywords Differential splicing ; Alternative splicing ; RNA-seq ; Uncertainty ; Biological variability ; Differentiation ; Biology (General) ; QH301-705.5 ; Genetics ; QH426-470
    Language English
    Publishing date 2018-03-01T00:00:00Z
    Publisher BMC
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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  10. Article ; Online: SARNAclust

    Ivan Dotu / Scott I Adamson / Benjamin Coleman / Cyril Fournier / Emma Ricart-Altimiras / Eduardo Eyras / Jeffrey H Chuang

    PLoS Computational Biology, Vol 14, Iss 3, p e

    Semi-automatic detection of RNA protein binding motifs from immunoprecipitation data.

    2018  Volume 1006078

    Abstract: RNA-protein binding is critical to gene regulation, controlling fundamental processes including splicing, translation, localization and stability, and aberrant RNA-protein interactions are known to play a role in a wide variety of diseases. However, ... ...

    Abstract RNA-protein binding is critical to gene regulation, controlling fundamental processes including splicing, translation, localization and stability, and aberrant RNA-protein interactions are known to play a role in a wide variety of diseases. However, molecular understanding of RNA-protein interactions remains limited; in particular, identification of RNA motifs that bind proteins has long been challenging, especially when such motifs depend on both sequence and structure. Moreover, although RNA binding proteins (RBPs) often contain more than one binding domain, algorithms capable of identifying more than one binding motif simultaneously have not been developed. In this paper we present a novel pipeline to determine binding peaks in crosslinking immunoprecipitation (CLIP) data, to discover multiple possible RNA sequence/structure motifs among them, and to experimentally validate such motifs. At the core is a new semi-automatic algorithm SARNAclust, the first unsupervised method to identify and deconvolve multiple sequence/structure motifs simultaneously. SARNAclust computes similarity between sequence/structure objects using a graph kernel, providing the ability to isolate the impact of specific features through the bulge graph formalism. Application of SARNAclust to synthetic data shows its capability of clustering 5 motifs at once with a V-measure value of over 0.95, while GraphClust achieves only a V-measure of 0.083 and RNAcontext cannot detect any of the motifs. When applied to existing eCLIP sets, SARNAclust finds known motifs for SLBP and HNRNPC and novel motifs for several other RBPs such as AGGF1, AKAP8L and ILF3. We demonstrate an experimental validation protocol, a targeted Bind-n-Seq-like high-throughput sequencing approach that relies on RNA inverse folding for oligo pool design, that can validate the components within the SLBP motif. Finally, we use this protocol to experimentally interrogate the SARNAclust motif predictions for protein ILF3. Our results support a newly identified partially ...
    Keywords Biology (General) ; QH301-705.5
    Subject code 006
    Language English
    Publishing date 2018-03-01T00:00:00Z
    Publisher Public Library of Science (PLoS)
    Document type Article ; Online
    Database BASE - Bielefeld Academic Search Engine (life sciences selection)

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