BMC Genomics 2008, 9:230 http://www.biomedcentral.com/1471-2164/9/230 studies to help define microbial species, to explore the genetic diversity within individual species, to study the evolutionary history of bacterial adaptations and to iden- tify genes potentially associated with virulence, transmis- sion or host specificity of a given microorganism [7-9]. These studies led to the concept of a bacterial pan-genome [10] consisting of the global gene pool of a given bacterial species, that could greatly exceed the gene repertoire of any individual strain [11]. This repertoire includes the core genome, defined as the pool of genes shared by all strains of a given species, and the dispensable genome constituted by genes present in some, but not all, strains of the same species [11]. The realization that the presence of certain genes could be variable or ubiquitous among members of a same species predates the genomics era. Campbell in an early review [12], identified "euchromo- somal" and "accessory" DNA and discussed the impor- tance of gene transfer in shaping the latter. Depending on the question addressed, one may be more concerned with the presence of genes characterizing the core genome, for instance to define microbial species, or with the comple- ment of the dispensable or accessory genome carried by particular groups of strains. Since a large number of viru- lence factors are carried by mobile genetic elements or are otherwise members of the accessory genome, the studies attempting to identify associations between genetic com- plement and virulence naturally focus on the genes not shared by all strains [7,9]. Microarrays used in aCGH experiments are frequently constructed based on the known genome sequence of one strain, which is used as a control in each experiment. Genomic DNAs of the control and test strains are labeled with two fluorochromes and hybridized onto the micro- array, which has spots identifying all genes of the refer- ence genome. After scanning and image analysis, the logarithm of the ratio (log-ratio or LR) of both fluorescent signals (test over control) is computed for each spot. Genes present in both genomes are expected to give a clear fluorescence signal in both channels (LR close to 0), whereas genes absent in the test sample will only have a signal in the control channel (negative LR) [1]. If several strains of a given species have been sequenced, then it is possible to design microarrays with reporter ele- ments representing more than just the genes in a single reference strain. The genomes of all sequenced strains can be used in microarray design. As more and more bacterial strains are sequenced, there is a clear trend towards the use of multistrain arrays [4,7,9]. In these cases, if only one of the sequenced strains is used as a control, in addition to detecting the presence or absence of genes found in the control, a multistrain array can now measure additions, i.e., those genes that are present in the test but absent in the control. The additions have positive LR values [2]. Alternatively, all strains used in microarray design can be used as control if an equimolar mix of their genomic DNA is labeled with the reference fluorochrome and hybridized together with the test. This mixed control provides at least a partial signal in all spots, in contrast to the single strain control option. After surveying published studies with multistrain arrays, it is clear that there is no universally accepted standard of which control to use in these experiments. Some studies have used the single strain control [7-9,13,14] while oth- ers adopted the mix control approach [15-17]. The former frequently argue that a multistrain mix control, while gen- erating a control signal for every spot on the microarray, leads to an increased signal intensity of core genome spots in the control channel and complicates data analysis based on ratios [7-9,13,14]. In spite of the multiple argu- ments invoked to support each of the approaches, we found that a study objectively comparing aCGH perform- ance of the single strain versus the mix control approach was lacking. To fill in this gap, we performed a comparative study with a multistrain array for Streptococcus pneumoniae, covering the genomes of three sequenced strains: TIGR4 (T) [18], R6 (R) [19] and G54 (G) [20]. We used two of these strains as tests (R and G) and hybridized them with two different controls: a single strain (T) or an equimolar mix of the three strains represented in the array (T+R+G). As the true lists of absent genes for each strain where known a priori in our experiments, we could evaluate the discriminatory power of a given rule to call a spot present or absent. Several statistical methods have been proposed to define this rule specially adequate to bacterial aCGH experiments [2,4,21,22]. Independently of the chosen method, the quality of the results is intrinsically related to the discriminatory power of the LR distribution. In princi- ple, differences found at the level of the LR distribution will be propagated through the results of every aCGH analysis method. Therefore, to better evaluate the impact of the choice of control we decided to evaluate LR distri- butions directly, through Receiver Operating Characteris- tics (ROC) analysis [23]. Using this analysis, the best LR threshold (above which spots are called present) was defined and characterized by its accuracy, sensitivity and specificity. We then explored the differences in these eval- uation parameters attributable to the choice of control sample. Our results show that the use of the mix control approach provide more discriminatory LR distributions, and, consequently, less errors in the classification of genes as present or absent in the studied strain. Page 2 of 11 (page number not for citation purposes)