TAM: a method for enrichment and depletion analysis of a microRNA category in a list of microRNAs.
BACKGROUND
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).


RESULTS
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.


CONCLUSIONS
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 http://cmbi.bjmu.edu.cn/tam.
Lu
Ming
M
Department of Biomedical Informatics, Peking University Health Science Center, Beijing, 100191, China.
Shi
Bing
B
Wang
Juan
J
Cao
Qun
Q
Cui
Qinghua
Q
D020869:Gene Expression Profiling; D015894:Genome, Human; D006801:Humans; D020407:Internet; D035683:MicroRNAs / Q000235:genetics*; D009203:Myocardial Infarction / Q000235:genetics*; D012984:Software
D035683:MicroRNAs