TY - JOUR T1 - The Evolutionary Analysis of Emerging Low Frequency HIV-1 CXCR4 Using Variants through Timeā€”An Ultra-Deep Approach A1 - Archer, John A1 - Rambaut, Andrew A1 - Taillon, Bruce E. A1 - Harrigan, P. Richard A1 - Lewis, Marilyn A1 - Robertson, David L. Y1 - 2010/12/16 N2 - Author Summary Due to high data volumes, error rates, and short sequence lengths, new sequencing technologies present a new challenge for computational biology. In addition, high-depth (or ultra-deep) datasets, for example from pathogens, contain exceptionally large amounts of variation over short genomes or genomic regions. Here we present software for the processing and downstream analysis of such short-read viral sequence data. We apply the software to the analysis of two HIV-1 infected individuals who did not respond optimally to the drug maraviroc. For each patient, pyrosequence data was available for five time points. In both cases we detect distinct clusters of low-frequency drug-insensitive variants that were present prior to maraviroc treatment and effectively unmasked by the removal of the drug-sensitive HIV. JF - PLOS Computational Biology JA - PLOS Computational Biology VL - 6 IS - 12 UR - https://doi.org/10.1371/journal.pcbi.1001022 SP - e1001022 EP - PB - Public Library of Science M3 - doi:10.1371/journal.pcbi.1001022 ER -