Automated FingerPrint Background removal: FPB
1 Istituto di Genomica Applicata (IGA), via J. Linussio 51, I-33100 Udine, Italy
2 Department of Mathematics and Computer Science, University of Udine, via delle Scienze 206, I-33100 Udine, Italy
3 Department of Agriculture and Environmental Sciences, University of Udine, via delle Scienze 208, I-33100 Udine, Italy
BMC Bioinformatics 2009, 10:127 doi:10.1186/1471-2105-10-127Published: 30 April 2009
The construction of a whole-genome physical map has been an essential component of numerous genome projects initiated since the inception of the Human Genome Project. Its usefulness has been proved for whole-genome shotgun projects as a post-assembly validation and recently it has also been used in the assembly step to constrain on BACs positions. Fingerprinting is usually the method of choice for construction of physical maps. A clone fingerprint is composed of true peaks representing real fragments and background peaks, mainly composed of E. coli genomic DNA, partial digestions, star activity by-products, and machine background. High-throughput fingerprinting leads to the production of thousands of BAC clone fingerprints per day. That is why background peaks removal has become an important issue and needs to be automatized, especially in capillary electrophoresis based fingerprints.
At the moment, the only tools available for such a task are GenoProfiler and its descendant FPMiner. The large variation in the quality of fingerprints that is usually present in large fingerprinting projects represents a major difficulty in the correct removal of background peaks that has only been partially addressed by the methods so far adopted that all require a long manual optimization of parameters. Thus, we implemented a new data-independent tool, FPB (FingerPrint Background removal), suitable for large scale projects as well as mapping of few clones.
FPB is freely available at http://www.appliedgenomics.org/tools.php webcite. FPB was used to remove the background from all fingerprints of three grapevine physical map projects. The first project consists of about 50,000 fingerprints, the second one consists of about 70,000 fingerprints, and the third one consists of about 45,000 fingerprints. In all cases a successful assembly was built.