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Published online 12 February 2004

Nucleic Acids Research, 2004, Vol. 32, No. 3 949-958
© 2004 Oxford University Press

Statistical analysis of over-represented words in human promoter sequences

Leonardo Mariño-Ramírez, John L. Spouge, Gavin C. Kanga and David Landsman*

Computational Biology Branch, National Center for Biotechnology Information, National Library of Medicine, National Institutes of Health, 8600 Rockville Pike, MSC 6075 Bethesda, MD 20894-6075, USA

*To whom correspondence should be addressed. Tel: +1 301 435 5981; Fax: +1 301 480 2288; Email: landsman{at}ncbi.nlm.nih.gov

The identification and characterization of regulatory sequence elements in the proximal promoter region of a gene can be facilitated by knowing the precise location of the transcriptional start site (TSS). Using known TSSs from over 5700 different human full-length cDNAs, this study extracted a set of 4737 distinct putative promoter regions (PPRs) from the human genome. Each PPR consisted of nucleotides from –2000 to +1000 bp, relative to the corresponding TSS. Since many regulatory regions contain short, highly conserved strings of less than 10 nucleotides, we counted eight-letter words within the PPRs, using z-scores and other related statistics to evaluate their over- and under-representation. Several over-represented eight-letter words have known biological functions described in the eukaryotic transcription factor database TRANSFAC; however, many did not. Besides calculating a P-value with the standard normal approximation associated with z-scores, we used two extra statistical controls to evaluate the significance of over-represented words. These controls have important implications for evaluating over- and under-represented words with z-scores.


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