|Pooled Genomic Indexing (PGI): analysis and design of experiments.
|Year of Publication
|Csuros, M, Milosavljevic, A
|J Comput Biol
|Animals, Chromosomes, Artificial, Bacterial, Computational Biology, Data Interpretation, Statistical, Mice, Phylogeny, Physical Chromosome Mapping, Probability, Rats, Research Design
Pooled Genomic Indexing (PGI) is a novel method for physical mapping of clones onto known sequences. PGI is carried out by pooling arrayed clones and generating shotgun sequence reads from the pools. The shotgun sequences are compared to a reference sequence. In the simplest case, clones are placed on an array and are pooled by rows and columns. If a shotgun sequence from a row pool and another shotgun sequence from a column pool match the reference sequence at a close distance, they are both assigned to the clone at the intersection of the two pools. Accordingly, the clone is mapped onto the region of the reference sequence between the two matches. A probabilistic model for PGI is developed, and several pooling designs are described and analyzed, including transversal designs and designs from linear codes. The probabilistic model and the pooling schemes are validated in simulated experiments where 625 rat bacterial artificial chromosome (BAC) clones and 207 mouse BAC clones are mapped onto homologous human sequence.
|J Comput Biol
|R01 HG02583-01 / HG / NHGRI NIH HHS / United States