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      Next-generation sequencing data interpretation: enhancing reproducibility and accessibility.

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      Publication date:
      Journal: Nature reviews. Genetics
      Keywords: Access to Information, Base Sequence, Data Interpretation, Statistical, Genetic Privacy, High-Throughput Nucleotide Sequencing, methods, trends, Humans, Molecular Sequence Data, Reproducibility of Results, Sequence Analysis, DNA

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          Abstract

          Areas of life sciences research that were previously distant from each other in ideology, analysis practices and toolkits, such as microbial ecology and personalized medicine, have all embraced techniques that rely on next-generation sequencing instruments. Yet the capacity to generate the data greatly outpaces our ability to analyse it. Existing sequencing technologies are more mature and accessible than the methodologies that are available for individual researchers to move, store, analyse and present data in a fashion that is transparent and reproducible. Here we discuss currently pressing issues with analysis, interpretation, reproducibility and accessibility of these data, and we present promising solutions and venture into potential future developments.

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          Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences

          Jeremy Goecks, Anton Nekrutenko, James E. Taylor (2010)
          Increased reliance on computational approaches in the life sciences has revealed grave concerns about how accessible and reproducible computation-reliant results truly are. Galaxy http://usegalaxy.org, an open web-based platform for genomic research, addresses these problems. Galaxy automatically tracks and manages data provenance and provides support for capturing the context and intent of computational methods. Galaxy Pages are interactive, web-based documents that provide users with a medium to communicate a complete computational analysis.
          Article 0 comments Cited 1410 times – based on 0 reviews     Review now
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            Exome sequencing of head and neck squamous cell carcinoma reveals inactivating mutations in NOTCH1.

            N. Agrawal, M Frederick, C. R. Pickering … (2011)
            Head and neck squamous cell carcinoma (HNSCC) is the sixth most common cancer worldwide. To explore the genetic origins of this cancer, we used whole-exome sequencing and gene copy number analyses to study 32 primary tumors. Tumors from patients with a history of tobacco use had more mutations than did tumors from patients who did not use tobacco, and tumors that were negative for human papillomavirus (HPV) had more mutations than did HPV-positive tumors. Six of the genes that were mutated in multiple tumors were assessed in up to 88 additional HNSCCs. In addition to previously described mutations in TP53, CDKN2A, PIK3CA, and HRAS, we identified mutations in FBXW7 and NOTCH1. Nearly 40% of the 28 mutations identified in NOTCH1 were predicted to truncate the gene product, suggesting that NOTCH1 may function as a tumor suppressor gene rather than an oncogene in this tumor type.
            Article 0 comments Cited 604 times – based on 0 reviews     Review now
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              Computational analysis of microarray data.

              J Quackenbush (2001)
              Microarray experiments are providing unprecedented quantities of genome-wide data on gene-expression patterns. Although this technique has been enthusiastically developed and applied in many biological contexts, the management and analysis of the millions of data points that result from these experiments has received less attention. Sophisticated computational tools are available, but the methods that are used to analyse the data can have a profound influence on the interpretation of the results. A basic understanding of these computational tools is therefore required for optimal experimental design and meaningful data analysis.
              Article 0 comments Cited 256 times – based on 0 reviews     Review now
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                Author and article information

                Journal
                PubMed ID:: 22898652
                DOI:: 10.1038/nrg3305

                ScienceOpen disciplines: Chemistry
                Keywords: Access to Information,Base Sequence,Data Interpretation, Statistical,Genetic Privacy,High-Throughput Nucleotide Sequencing,methods,trends,Humans,Molecular Sequence Data,Reproducibility of Results,Sequence Analysis, DNA
                Data availability:
                ScienceOpen disciplines: Chemistry
                Keywords: Access to Information, Base Sequence, Data Interpretation, Statistical, Genetic Privacy, High-Throughput Nucleotide Sequencing, methods, trends, Humans, Molecular Sequence Data, Reproducibility of Results, Sequence Analysis, DNA

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