miRanalyzer: a microRNA detection and analysis tool for next-generation sequencing experiments

被引:205
作者
Hackenberg, Michael [1 ]
Sturm, Martin [2 ]
Langenberger, David [3 ,4 ]
Manuel Falcon-Perez, Juan [5 ]
Aransay, Ana M. [1 ]
机构
[1] CIC bioGUNE, Funct Genom Unit, CIBERehd, Derio 48160, Bizkaia, Spain
[2] German Res Ctr Environm Hlth, Inst Bioinformat & Syst Biol, D-85764 Neuherberg, Germany
[3] Tech Univ Munich, Wissensch Zentrum Weihenstephan, Dept Genome Oriented Bioinformat, D-85350 Freising Weihenstephan, Germany
[4] Univ Leipzig, Dept Comp Sci, Bioinformat Grp, D-04107 Leipzig, Germany
[5] CIC bioGUNE, CIBERehd, Metabol Unit, Derio 48160, Bizkaia, Spain
关键词
IDENTIFICATION; CLASSIFICATION; PREDICTION; GENES; REAL;
D O I
10.1093/nar/gkp347
中图分类号
Q5 [生物化学]; Q7 [分子生物学];
学科分类号
071010 ; 081704 ;
摘要
Next-generation sequencing allows now the sequencing of small RNA molecules and the estimation of their expression levels. Consequently, there will be a high demand of bioinformatics tools to cope with the several gigabytes of sequence data generated in each single deep-sequencing experiment. Given this scene, we developed miRanalyzer, a web server tool for the analysis of deep-sequencing experiments for small RNAs. The web server tool requires a simple input file containing a list of unique reads and its copy numbers (expression levels). Using these data, miRanalyzer (i) detects all known microRNA sequences annotated in miRBase, (ii) finds all perfect matches against other libraries of transcribed sequences and (iii) predicts new microRNAs. The prediction of new microRNAs is an especially important point as there are many species with very few known microRNAs. Therefore, we implemented a highly accurate machine learning algorithm for the prediction of new microRNAs that reaches AUC values of 97.9% and recall values of up to 75% on unseen data. The web tool summarizes all the described steps in a single output page, which provides a comprehensive overview of the analysis, adding links to more detailed output pages for each analysis module. miRanalyzer is available at http://web.bioinformatics.cicbiogune.es/microRNA/.
引用
收藏
页码:W68 / W76
页数:9
相关论文
共 23 条
[1]  
Bagasra O, 2004, J MOL HISTOL, V35, P545
[2]   Identification of hundreds of conserved and nonconserved human microRNAs [J].
Bentwich, I ;
Avniel, A ;
Karov, Y ;
Aharonov, R ;
Gilad, S ;
Barad, O ;
Barzilai, A ;
Einat, P ;
Einav, U ;
Meiri, E ;
Sharon, E ;
Spector, Y ;
Bentwich, Z .
NATURE GENETICS, 2005, 37 (07) :766-770
[3]   Phylogenetic shadowing and computational identification of human microRNA genes [J].
Berezikov, E ;
Guryev, V ;
van de Belt, J ;
Wienholds, E ;
Plasterk, RHA ;
Cuppen, E .
CELL, 2005, 120 (01) :21-24
[4]   Many novel mammalian microRNA candidates identified by extensive cloning and RAKE analysis [J].
Berezikov, Eugene ;
van Tetering, Geert ;
Verheul, Mark ;
van de Belt, Jose ;
van Laake, Linda ;
Vos, Joost ;
Verloop, Robert ;
van de Wetering, Marc ;
Guryev, Victor ;
Takada, Shuji ;
van Zonneveld, Anton Jan ;
Mano, Hiroyuki ;
Plasterk, Ronald ;
Cuppen, Edwin .
GENOME RESEARCH, 2006, 16 (10) :1289-1298
[5]   Random forests [J].
Breiman, L .
MACHINE LEARNING, 2001, 45 (01) :5-32
[6]   MicroRNA targets in Drosophila [J].
Anton J Enright ;
Bino John ;
Ulrike Gaul ;
Thomas Tuschl ;
Chris Sander ;
Debora S Marks .
Genome Biology, 5 (1)
[7]   Discovering microRNAs from deep sequencing data using miRDeep [J].
Friedlaender, Marc R. ;
Chen, Wei ;
Adamidi, Catherine ;
Maaskola, Jonas ;
Einspanier, Ralf ;
Knespel, Signe ;
Rajewsky, Nikolaus .
NATURE BIOTECHNOLOGY, 2008, 26 (04) :407-415
[8]   Rfam: updates to the RNA families database [J].
Gardner, Paul P. ;
Daub, Jennifer ;
Tate, John G. ;
Nawrocki, Eric P. ;
Kolbe, Diana L. ;
Lindgreen, Stinus ;
Wilkinson, Adam C. ;
Finn, Robert D. ;
Griffiths-Jones, Sam ;
Eddy, Sean R. ;
Bateman, Alex .
NUCLEIC ACIDS RESEARCH, 2009, 37 :D136-D140
[9]   Galaxy: A platform for interactive large-scale genome analysis [J].
Giardine, B ;
Riemer, C ;
Hardison, RC ;
Burhans, R ;
Elnitski, L ;
Shah, P ;
Zhang, Y ;
Blankenberg, D ;
Albert, I ;
Taylor, J ;
Miller, W ;
Kent, WJ ;
Nekrutenko, A .
GENOME RESEARCH, 2005, 15 (10) :1451-1455
[10]  
Griffiths-Jones Sam, 2006, V342, P129, DOI 10.1385/1-59745-123-1:129