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Open Access Highly Accessed Open Badges Methodology article

TAM: A method for enrichment and depletion analysis of a microRNA category in a list of microRNAs

Ming Lu1, Bing Shi12, Juan Wang1, Qun Cao1 and Qinghua Cui1*

Author Affiliations

1 Department of Biomedical Informatics, Peking University Health Science Center, Beijing, 100191, China

2 Department of Cardiology, Beijing Military General Hospital, Beijing, 100700, China

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BMC Bioinformatics 2010, 11:419  doi:10.1186/1471-2105-11-419

Published: 9 August 2010



MicroRNAs (miRNAs) are a class of important gene regulators. The number of identified miRNAs has been increasing dramatically in recent years. An emerging major challenge is the interpretation of the genome-scale miRNA datasets, including those derived from microarray and deep-sequencing. It is interesting and important to know the common rules or patterns behind a list of miRNAs, (i.e. the deregulated miRNAs resulted from an experiment of miRNA microarray or deep-sequencing).


For the above purpose, this study presents a method and develops a tool (TAM) for annotations of meaningful human miRNAs categories. We first integrated miRNAs into various meaningful categories according to prior knowledge, such as miRNA family, miRNA cluster, miRNA function, miRNA associated diseases, and tissue specificity. Using TAM, given lists of miRNAs can be rapidly annotated and summarized according to the integrated miRNA categorical data. Moreover, given a list of miRNAs, TAM can be used to predict novel related miRNAs. Finally, we confirmed the usefulness and reliability of TAM by applying it to deregulated miRNAs in acute myocardial infarction (AMI) from two independent experiments.


TAM can efficiently identify meaningful categories for given miRNAs. In addition, TAM can be used to identify novel miRNA biomarkers. TAM tool, source codes, and miRNA category data are freely available at webcite.