sRNAtoolboxVM: Small RNA Analysis in a Virtual Machine
High-throughput sequencing (HTS) data for small RNAs (noncoding RNA molecules that are 20–250 nucleotides in length) can now be routinely generated by minimally equipped wet laboratories; however, the bottleneck in HTS-based research has shifted now to the analysis of such huge amount of data. One of the reasons is that many analysis types require a Linux environment but computers, system administrators, and bioinformaticians suppose additional costs that often cannot be afforded by small to mid-sized groups or laboratories. Web servers are an alternative that can be used if the data is not subjected to privacy issues (what very often is an important issue with medical data). However, in any case they are less flexible than stand-alone programs limiting the number of workflows and analysis types that can be carried out.
We show in this protocol how virtual machines can be used to overcome those problems and limitations. sRNAtoolboxVM is a virtual machine that can be executed on all common operating systems through virtualization programs like VirtualBox or VMware, providing the user with a high number of preinstalled programs like sRNAbench for small RNA analysis without the need to maintain additional servers and/or operating systems.
Key wordsSmall RNA Bioinformatics Next generation sequencing Virtual machine
- 6.Buck AH, Coakley G, Simbari F, McSorley HJ, Quintana JF, Le Bihan T, Kumar S, Abreu-Goodger C, Lear M, Harcus Y, Ceroni A, Babayan SA, Blaxter M, Ivens A, Maizels RM (2014) Exosomes secreted by nematode parasites transfer small RNAs to mammalian cells and modulate innate immunity. Nat Commun 5:5488CrossRefPubMedPubMedCentralGoogle Scholar
- 12.The SRA knowledge base, NCBI help manual. Staff SRAS: using the SRA toolkit to convert .sra files into other formats. 2011 Bethesda (MD)Google Scholar
- 14.Fromm B, Billipp T, Peck LE, Johansen M, Tarver JE, King BL, Newcomb JM, Sempere LF, Flatmark K, Hovig E, Peterson KJ (2015) A uniform system for the annotation of vertebrate microRNA genes and the evolution of the human microRNAome. Annu Rev Genet 49:213–242CrossRefPubMedPubMedCentralGoogle Scholar
- 17.Agarwal V, Bell GW, Nam J-W, Bartel DP (2015) Predicting effective microRNA target sites in mammalian mRNAs. Elife 4 Google Scholar
- 25.Wu H-J, Ma Y-K, Chen T, Wang M, Wang X-J: PsRobot (2012) A web-based plant small RNA meta-analysis toolbox. Nucleic Acids Res 40, W22–W28.Google Scholar