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Title
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BatchGenAna: a batch platform for large-scale genomic analysis of mammalian small RNAs
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Authors
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Xiaomin Ying1, You Jung Kim2, Yiqing Mao3, Ming Liu4, Yanyan Hou1, Hua Li1, Xiaolei Wang3, Yalin Zhao1, Dongsheng Zhao3, Jignesh M. Patel2, Wuju Li1*
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Affiliation
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1Center of Computational Biology, Beijing Institute of Basic Medical Sciences, Beijing 100850, China; 2Department of Electrical Engineering and Computer Science, University of Michigan, Ann Arbor, MI 48109, USA; 3Beijing Institute of Health Administration and Medicine Information, Beijing 100850, China; 4Beijing Medical Library, Beijing 100039, China
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Article Type
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Software
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Date
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received January 21, 2009; accepted March 06, 2009; published April 21, 2009
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Abstract |
An increasing number of small RNAs have been discovered in mammals. However, their primary transcripts and upstream regulatory networks remain largely to be determined. Genomic analysis of small RNAs facilitates identification of their primary transcripts, and hence contributes to researches of their upstream regulatory networks. We here report a batch platform, BatchGenAna, which is specifically designed for large-scale genomic analysis of mammalian small RNAs. It can map and annotate for as many as 1000 small RNAs or 10,000 genomic loci of small RNAs at a time. It provides genomic features including RefSeq genes, mRNAs, ESTs and repeat elements in tabular and graphical results. It also allows extracting flanking sequences of submitted queries, specified genomic regions and host transcripts, which facilitates subsequent analysis such as scanning transcription factor binding sites in upstream sequences and poly(A) signals in downstream sequences. Besides small RNA fields, BatchGenAna can also be applied to other research fields, e.g. in silico analysis of target genes of transcription factors.
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Keywords |
small RNA; genomic analysis; primary transcript | |
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Availability |
The platform is freely available at http://biosrv1.bmi.ac.cn/BatchGenAna | |
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Citation |
Ying et al. Bioinformation 3(8): 346-348 (2009) | |
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Edited by |
P. Kangueane
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ISSN |
0973-2063
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Publisher |
Biomedical Informatics
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License
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This is an Open Access article which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly credited. This is distributed under the terms of the Creative Commons Attribution License.
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