Tony Håndstad

• Kornacker, K; Rye, Morten Beck; Håndstad, Tony & Drabløs, Finn (2012). The Triform algorithm: improved sensitivity and specificity in ChIP-Seq peak finding. BMC Bioinformatics. ISSN 1471-2105. 13. doi: 10.1186/1471-2105-13-176. Full text in Research Archive
• Håndstad, Tony; Rye, Morten Beck; Mocnik, Rok; Drabløs, Finn & Sætrom, Pål (2012). Cell-type specificity of ChIP-predicted transcription factor binding sites. BMC Genomics. ISSN 1471-2164. 13. doi: 10.1186/1471-2164-13-372. Full text in Research Archive
• Rye, Morten Beck; Sætrom, Pål; Håndstad, Tony & Drabløs, Finn (2011). Clustered ChIP-Seq-defined transcription factor binding sites and histone modifications map distinct classes of regulatory elements. BMC Biology. ISSN 1741-7007. 9. doi: 10.1186/1741-7007-9-80. Full text in Research Archive
• Håndstad, Tony; Rye, Morten Beck; Drabløs, Finn & Sætrom, Pål (2011). A ChIP-Seq Benchmark Shows That Sequence Conservation Mainly Improves Detection of Strong Transcription Factor Binding Sites. PLOS ONE. ISSN 1932-6203. 6(4). doi: 10.1371/journal.pone.0018430. Full text in Research Archive
• Håndstad, Tony; Hestnes, Arne Johan Husebø & Sætrom, Pål (2007). Motif kernel generated by genetic programming improves remote homology and fold detection. BMC Bioinformatics. ISSN 1471-2105. 8. doi: 10.1186/1471-2105-8-23. Full text in Research Archive

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• Jimenez-Ruiz, Ernesto; Hovland, Dag; Slaughter, Laura; Håndstad, Tony & Waaler, Arild (2017). On adopting ontology alignment techniques within the phenotype acquisition process. CEUR Workshop Proceedings. ISSN 1613-0073. 2042, p. 1–2.
• Eike, Morten Christoph; Seljebotn, Svein Tore; Nafstad, Eidi; Håndstad, Tony; Fontenelle, Hugues & Honneffer, David Jacob [Show all 9 contributors for this article] (2016). Ella: decision support and structured data in clinical variant classification.
• Eike, Morten Christoph; Skorve, Espen; Håndstad, Tony; Fontenelle, Hugues; Børsting, Jorun & Aanestad, Margunn [Show all 9 contributors for this article] (2014). GenAP workbench: aiding variant classification in clinical diagnostic settings.
• Eike, Morten Christoph; Håndstad, Tony; Nafstad, Eidi; Hughes, Timothy; Grünfeld, Thomas & Undlien, Dag Erik (2013). GenAP: automated analysis of genetic HTS data for clinical diagnostic use.
• Kornacker, Karl; Rye, Morten Beck; Håndstad, Tony & Drabløs, Finn (2013). The Triform algorithm: improved sensitivity and specificity in ChIP-Seq peak finding.
• Drabløs, Finn; Kornacker, Karl; Rye, Morten Beck & Håndstad, Tony (2012). The Triform algorithm: improved sensitivity and specificity in ChIP-Seq peak finding.
• Eike, Morten Christoph; Lærum, Hallvard; Hughes, Timothy; Håndstad, Tony; Bremer, Sara & Bergan, Stein [Show all 10 contributors for this article] (2012). GenAP: a platform for clinical genetic analysis of high-throughput sequencing data. Show summary

  The introduction of high-throughput sequencing (HTS) into clinical practice poses great challenges in terms of analytic resources, integration and data security. The project Norwegian clinical genetic Analysis Platform (genAP) was initiated as a response to these challenges, aiming to establish a centralised infrastructure for secure storage and analysis of human sequencing data, with possibilities for disseminated clinical use. GenAP is a collaborative project between Oslo University Hospital and the University of Oslo, with implementation of the system in a high-performance computing environment. As part of this project, we are in the process of establishing pilot HTS pipelines for a set of clinical packages, each with a defined set of targeted genes. The pilots cover diagnostic, prognostic and pharmacogenetic areas, including cardiomyopathies, breast cancer and tacrolimus dosage, respectively. Initially, the pipelines involve data for a limited set of candidate genes, but the system will be scalable to exome and whole-genome data for a large number of patients. To reduce the workload associated with manual analysis, we have sought to achieve a high degree of automation, including variant annotation and quality control, filtering and prioritisation based on public resources, identification of previously classified variants, and standardisation of report information structure for integration with existing medical journal systems. The pilot phase includes comparing the performance of HTS to conventional methods, building a database of genetic variants adapted to our patient populations and real-world testing using collaborating clinicians. The experiences gained will be used to expand to other clinical packages, and the ultimate goal is to introduce the system in the clinic. Complementing the genetic, bioinformatic and clinical issues, the project also addresses legal, ethical and organizational issues encountered when HTS is deployed in large scale clinical decision making. This presentation will demonstrate the overall architecture of our system and present initial experiences with the pilot systems.

• Rye, Morten Beck; Sætrom, Pål; Håndstad, Tony & Drabløs, Finn (2011). Clusters of ChIP-Seq defined transcription factor binding sites map regulatory elelemnts in the human genome.
• Rye, Morten Beck; Drabløs, Finn; Sætrom, Pål & Håndstad, Tony (2011). Epigenetic Influence on Cell-type specific peaks from ChIP-Seq data.
• Håndstad, Tony (2011). Cell type specificity of ChIP-predicted transcription factor binding sites.
• Håndstad, Tony (2011). Cell type specificity of ChIP-predicted transcription factor binding sites.
• Håndstad, Tony (2011). Cell-type specificity and noise for transcription factor binding sites predicted by ChIP-sequencing.
• Håndstad, Tony (2009). Modeling of gene regulatory networks.
• Håndstad, Tony (2009). Modeling of gene regulatory networks.

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