title: Indexes of large genome collections on a PC.
abstract: The availability of thousands of individual genomes of one species should boost rapid progress in personalized medicine or understanding of the interaction between genotype and phenotype, to name a few applications. A key operation useful in such analyses is aligning sequencing reads against a collection of genomes, which is costly with the use of existing algorithms due to their large memory requirements. We present MuGI, Multiple Genome Index, which reports all occurrences of a given pattern, in exact and approximate matching model, against a collection of thousand(s) genomes. Its unique feature is the small index size, which is customisable. It fits in a standard computer with 16-32 GB, or even 8 GB, of RAM, for the 1000GP collection of 1092 diploid human genomes. The solution is also fast. For example, the exact matching queries (of average length 150 bp) are handled in average time of 39 µs and with up to 3 mismatches in 373 µs on the test PC with the index size of 13.4 GB. For a smaller index, occupying 7.4 GB in memory, the respective times grow to 76 µs and 917 µs. Software is available at http://sun.aei.polsl.pl/mugi under a free license. Data S1 is available at PLOS One online.
authors.affiliation: Institute of Informatics, Silesian University of Technology, Gliwice, Poland.
authors.forename: Agnieszka
authors.initials: A
authors.lastname: Danek
authors.affiliation: Institute of Informatics, Silesian University of Technology, Gliwice, Poland.
authors.forename: Sebastian
authors.initials: S
authors.lastname: Deorowicz
authors.affiliation: Institute of Applied Computer Science, Lodz University of Technology, Łódź, Poland.
authors.forename: Szymon
authors.initials: S
authors.lastname: Grabowski
mesh_terms: D000043:Abstracting and Indexing; D000465:Algorithms; D019295:Computational Biology / Q000379:methods; D003201:Computers; D066264:Datasets as Topic; D016678:Genome; D023281:Genomics / Q000379:methods