O-miner: an integrative platform for automated analysis and mining of -omics data

被引:9
作者
Cutts, Rosalind J. [1 ]
Ullah, Abu Z. Dayem [1 ]
Sangaralingam, Ajanthah [1 ]
Gadaleta, Emanuela [1 ]
Lemoine, Nicholas R. [1 ]
Chelala, Claude [1 ]
机构
[1] Queen Mary Univ London, Barts Canc Inst, Ctr Mol Oncol, London EC1M 6BQ, England
关键词
FALSE DISCOVERY RATE; ARRAY CGH DATA; ALGORITHM; GENES; MODEL;
D O I
10.1093/nar/gks432
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
High-throughput profiling has generated massive amounts of data across basic, clinical and translational research fields. However, open source comprehensive web tools for analysing data obtained from different platforms and technologies are still lacking. To fill this gap and the unmet computational needs of ongoing research projects, we developed O-miner, a rapid, comprehensive, efficient web tool that covers all the steps required for the analysis of both transcriptomic and genomic data starting from raw image files through in-depth bioinformatics analysis and annotation to biological knowledge extraction. O-miner was developed from a biologist end-user perspective. Hence, it is as simple to use as possible within the confines of the complexity of the data being analysed. It provides a strong analytical suite able to overlay and harness large, complicated, raw and heterogeneous sets of profiles with biological/clinical data. Biologists can use O-miner to analyse and integrate different types of data and annotations to build knowledge of relevant altered mechanisms and pathways in order to identify and prioritize novel targets for further biological validation. Here we describe the analytical workflows currently available using O-miner and present examples of use. O-miner is freely available at www.o-miner.org.
引用
收藏
页码:W560 / W568
页数:9
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