Viral Population Estimation Using Pyrosequencing Export

@article{citeulike:2908497, abstract = {The diversity of virus populations within single infected hosts presents a major difficulty for the natural immune response as well as for vaccine design and antiviral drug therapy. Recently developed pyrophosphate-based sequencing technologies (pyrosequencing) can be used for quantifying this diversity by ultra-deep sequencing of virus samples. We present computational methods for the analysis of such sequence data and apply these techniques to pyrosequencing data obtained from HIV populations within patients harboring drug-resistant virus strains. Our main result is the estimation of the population structure of the sample from the pyrosequencing reads. This inference is based on a statistical approach to error correction, followed by a combinatorial algorithm for constructing a minimal set of haplotypes that explain the data. Using this set of explaining haplotypes, we apply a statistical model to infer the frequencies of the haplotypes in the population via an expectation\^{a}€ ” maximization (EM) algorithm. We demonstrate that pyrosequencing reads allow for effective population reconstruction by extensive simulations and by comparison to 165 sequences obtained directly from clonal sequencing of four independent, diverse HIV populations. Thus, pyrosequencing can be used for cost-effective estimation of the structure of virus populations, promising new insights into viral evolutionary dynamics and disease control strategies.}, address = {Department of Statistics, University of Chicago, Chicago, Illinois, United States of America. eriksson@galton.uchicago.edu}, author = {Eriksson, Nicholas and Pachter, Lior and Mitsuya, Yumi and Rhee, Soo-Yon and Wang, Chunlin and Gharizadeh, Baback and Ronaghi, Mostafa and Shafer, Robert W. and Beerenwinkel, Niko}, citeulike-article-id = {2908497}, citeulike-linkout-0 = {http://dx.doi.org/10.1371/journal.pcbi.1000074}, citeulike-linkout-1 = {http://view.ncbi.nlm.nih.gov/pubmed/18437230}, citeulike-linkout-2 = {http://www.hubmed.org/display.cgi?uids=18437230}, comment = {Referenced in the manual for cufflinks http://cufflinks.cbcb.umd.edu/ for transcript assembly.}, day = {9}, doi = {10.1371/journal.pcbi.1000074}, issn = {1553-7358}, journal = {PLoS Comput Biol}, month = {May}, number = {5}, pages = {e1000074+}, posted-at = {2009-10-09 22:56:27}, priority = {2}, publisher = {Public Library of Science}, title = {Viral Population Estimation Using Pyrosequencing}, url = {http://dx.doi.org/10.1371/journal.pcbi.1000074}, volume = {4}, year = {2008} }

TY - JOUR ID - citeulike:2908497 L3 - citeulike-article-id:2908497 N2 - The diversity of virus populations within single infected hosts presents a major difficulty for the natural immune response as well as for vaccine design and antiviral drug therapy. Recently developed pyrophosphate-based sequencing technologies (pyrosequencing) can be used for quantifying this diversity by ultra-deep sequencing of virus samples. We present computational methods for the analysis of such sequence data and apply these techniques to pyrosequencing data obtained from HIV populations within patients harboring drug-resistant virus strains. Our main result is the estimation of the population structure of the sample from the pyrosequencing reads. This inference is based on a statistical approach to error correction, followed by a combinatorial algorithm for constructing a minimal set of haplotypes that explain the data. Using this set of explaining haplotypes, we apply a statistical model to infer the frequencies of the haplotypes in the population via an expectation–maximization (EM) algorithm. We demonstrate that pyrosequencing reads allow for effective population reconstruction by extensive simulations and by comparison to 165 sequences obtained directly from clonal sequencing of four independent, diverse HIV populations. Thus, pyrosequencing can be used for cost-effective estimation of the structure of virus populations, promising new insights into viral evolutionary dynamics and disease control strategies. IS - 5 JF - PLoS Comput Biol SN - 1553-7358 AD - Department of Statistics, University of Chicago, Chicago, Illinois, United States of America. eriksson@galton.uchicago.edu TI - Viral Population Estimation Using Pyrosequencing PB - Public Library of Science VL - 4 SP - e1000074 N1 - Referenced in the manual for cufflinks http://cufflinks.cbcb.umd.edu/ for transcript assembly. AU - Eriksson, Nicholas AU - Pachter, Lior AU - Mitsuya, Yumi AU - Rhee, Soo-Yon AU - Wang, Chunlin AU - Gharizadeh, Baback AU - Ronaghi, Mostafa AU - Shafer, Robert AU - Beerenwinkel, Niko PY - 2008/05/09/ UR - http://dx.doi.org/10.1371/journal.pcbi.1000074 ER -