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000139797 1001_ $$0P:(DE-2719)2811127$$aRahman, Raza-Ur$$b0$$eFirst author$$udzne
000139797 245__ $$aOasis 2: improved online analysis of small RNA-seq data.
000139797 260__ $$aHeidelberg$$bSpringer$$c2018
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000139797 520__ $$aSmall 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.
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000139797 650_7 $$2NLM Chemicals$$aMicroRNAs
000139797 650_7 $$2NLM Chemicals$$aRNA, Small Untranslated
000139797 650_2 $$2MeSH$$aBase Sequence
000139797 650_2 $$2MeSH$$aGene Expression Profiling
000139797 650_2 $$2MeSH$$aHigh-Throughput Nucleotide Sequencing
000139797 650_2 $$2MeSH$$aMicroRNAs: genetics
000139797 650_2 $$2MeSH$$aRNA, Small Untranslated: genetics
000139797 650_2 $$2MeSH$$aSequence Analysis, RNA: methods
000139797 650_2 $$2MeSH$$aSoftware
000139797 650_2 $$2MeSH$$aStatistics as Topic: methods
000139797 7001_ $$0P:(DE-2719)2811361$$aGautam, Abhivyakti$$b1$$udzne
000139797 7001_ $$0P:(DE-2719)2811972$$aBethune, Jörn$$b2$$udzne
000139797 7001_ $$0P:(DE-2719)2811813$$aSattar, Abdul$$b3$$udzne
000139797 7001_ $$0P:(DE-2719)2811935$$aFiosins, Maksims$$b4$$udzne
000139797 7001_ $$0P:(DE-2719)2812133$$aMagruder, Daniel Sumner$$b5$$udzne
000139797 7001_ $$0P:(DE-2719)2810626$$aCapece, Vincenzo$$b6$$udzne
000139797 7001_ $$0P:(DE-2719)2810755$$aShomroni, Orr$$b7$$udzne
000139797 7001_ $$0P:(DE-2719)2810547$$aBonn, Stefan$$b8$$eLast author$$udzne
000139797 77318 $$2Crossref$$3journal-article$$a10.1186/s12859-018-2047-z$$b : Springer Science and Business Media LLC, 2018-02-14$$n1$$p54$$tBMC Bioinformatics$$v19$$x1471-2105$$y2018
000139797 773__ $$0PERI:(DE-600)2041484-5$$a10.1186/s12859-018-2047-z$$gVol. 19, no. 1, p. 54$$n1$$p54$$q19:1<54$$tBMC bioinformatics$$v19$$x1471-2105$$y2018
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