Next-generation sequencing data interpretation: enhancing reproducibility and accessibility.
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.
Huck Institutes of the Life Sciences and the Department of Biochemistry and Molecular Biology, Penn State University, Wartik 505, University Park, Pennsylvania 16802, USA. anton@bx.psu.edul
Anton
A
Nekrutenko
James
J
Taylor
D022126:Access to Information; D001483:Base Sequence; D003627:Data Interpretation, Statistical; D030661:Genetic Privacy; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods* / Q000639:trends*; D006801:Humans; D008969:Molecular Sequence Data; D015203:Reproducibility of Results; D017422:Sequence Analysis, DNA / Q000379:methods* / Q000639:trends*