%0 Journal Article
%A Rahman, Raza-Ur
%A Gautam, Abhivyakti
%A Bethune, Jörn
%A Sattar, Abdul
%A Fiosins, Maksims
%A Magruder, Daniel Sumner
%A Capece, Vincenzo
%A Shomroni, Orr
%A Bonn, Stefan
%T Oasis 2: improved online analysis of small RNA-seq data.
%J BMC bioinformatics
%V 19
%N 1
%@ 1471-2105
%C Heidelberg
%I Springer
%M DZNE-2020-06119
%P 54
%D 2018
%X Small RNA molecules play important roles in many biological processes and their dysregulation or dysfunction can cause disease. The current method of choice for genome-wide sRNA expression profiling is deep sequencing.Here we present Oasis 2, which is a new main release of the Oasis web application for the detection, differential expression, and classification of small RNAs in deep sequencing data. Compared to its predecessor Oasis, Oasis 2 features a novel and speed-optimized sRNA detection module that supports the identification of small RNAs in any organism with higher accuracy. Next to the improved detection of small RNAs in a target organism, the software now also recognizes potential cross-species miRNAs and viral and bacterial sRNAs in infected samples. In addition, novel miRNAs can now be queried and visualized interactively, providing essential information for over 700 high-quality miRNA predictions across 14 organisms. Robust biomarker signatures can now be obtained using the novel enhanced classification module.Oasis 2 enables biologists and medical researchers to rapidly analyze and query small RNA deep sequencing data with improved precision, recall, and speed, in an interactive and user-friendly environment.Oasis 2 is implemented in Java, J2EE, mysql, Python, R, PHP and JavaScript. It is freely available at https://oasis.dzne.de.
%K Base Sequence
%K Gene Expression Profiling
%K High-Throughput Nucleotide Sequencing
%K MicroRNAs: genetics
%K RNA, Small Untranslated: genetics
%K Sequence Analysis, RNA: methods
%K Software
%K Statistics as Topic: methods
%K MicroRNAs (NLM Chemicals)
%K RNA, Small Untranslated (NLM Chemicals)
%F PUB:(DE-HGF)16
%9 Journal Article
%$ pmid:29444641
%2 pmc:PMC5813365
%R 10.1186/s12859-018-2047-z
%U https://pub.dzne.de/record/139797