title: Error correction and statistical analyses for intra-host comparisons of feline immunodeficiency virus diversity from high-throughput sequencing data.
abstract: BACKGROUND
  Infection with feline immunodeficiency virus (FIV) causes an immunosuppressive disease whose consequences are less severe if cats are co-infected with an attenuated FIV strain (PLV). We use virus diversity measurements, which reflect replication ability and the virus response to various conditions, to test whether diversity of virulent FIV in lymphoid tissues is altered in the presence of PLV. Our data consisted of the 3' half of the FIV genome from three tissues of animals infected with FIV alone, or with FIV and PLV, sequenced by 454 technology.
  
  
  RESULTS
  Since rare variants dominate virus populations, we had to carefully distinguish sequence variation from errors due to experimental protocols and sequencing. We considered an exponential-normal convolution model used for background correction of microarray data, and modified it to formulate an error correction approach for minor allele frequencies derived from high-throughput sequencing. Similar to accounting for over-dispersion in counts, this accounts for error-inflated variability in frequencies - and quite effectively reproduces empirically observed distributions. After obtaining error-corrected minor allele frequencies, we applied ANalysis Of VAriance (ANOVA) based on a linear mixed model and found that conserved sites and transition frequencies in FIV genes differ among tissues of dual and single infected cats. Furthermore, analysis of minor allele frequencies at individual FIV genome sites revealed 242 sites significantly affected by infection status (dual vs. single) or infection status by tissue interaction. All together, our results demonstrated a decrease in FIV diversity in bone marrow in the presence of PLV. Importantly, these effects were weakened or undetectable when error correction was performed with other approaches (thresholding of minor allele frequencies; probabilistic clustering of reads). We also queried the data for cytidine deaminase activity on the viral genome, which causes an asymmetric increase in G to A substitutions, but found no evidence for this host defense strategy.
  
  
  CONCLUSIONS
  Our error correction approach for minor allele frequencies (more sensitive and computationally efficient than other algorithms) and our statistical treatment of variation (ANOVA) were critical for effective use of high-throughput sequencing data in understanding viral diversity. We found that co-infection with PLV shifts FIV diversity from bone marrow to lymph node and spleen.
authors.affiliation: Department of Statistics, The Pennsylvania State University, University Park, PA, 16802, USA. ywl5222@psu.edu.|The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, 16802, USA. ywl5222@psu.edu.
authors.forename: Yang
authors.initials: Y
authors.lastname: Liu
authors.affiliation: Department of Statistics, The Pennsylvania State University, University Park, PA, 16802, USA. chiaro@stat.psu.edu.|The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, 16802, USA. chiaro@stat.psu.edu.
authors.forename: Francesca
authors.initials: F
authors.lastname: Chiaromonte
authors.affiliation: Bioinformatics Institute, School of Biological Sciences, University of Auckland, Auckland, 1142, New Zealand. h.ross@auckland.ac.nz.
authors.forename: Howard
authors.initials: H
authors.lastname: Ross
authors.affiliation: Department of Computer Science and Engineering, The Pennsylvania State University, University Park, PA, 16802, USA. raunaq@psu.edu.
authors.forename: Raunaq
authors.initials: R
authors.lastname: Malhotra
authors.affiliation: Department of Biology, The Pennsylvania State University, University Park, PA, 16802, USA. Daniel.Elleder@img.cas.cz.|The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, 16802, USA. Daniel.Elleder@img.cas.cz.|Current address: Institute of Molecular Genetics, Academy of Sciences of the Czech Republic, Videnska 1083, Prague, 14000, Czech Republic. Daniel.Elleder@img.cas.cz.
authors.forename: Daniel
authors.initials: D
authors.lastname: Elleder
authors.affiliation: Department of Biology, The Pennsylvania State University, University Park, PA, 16802, USA. mposs@bx.psu.edu.|Department of Veterinary and Biomedical Sciences, The Pennsylvania State University, University Park, PA, 16802, USA. mposs@bx.psu.edu.|The Huck Institutes of the Life Sciences, The Pennsylvania State University, University Park, PA, 16802, USA. mposs@bx.psu.edu.
authors.forename: Mary
authors.initials: M
authors.lastname: Poss
mesh_terms: D000465:Algorithms; D000818:Animals; D002371:Cat Diseases / Q000235:genetics / Q000276:immunology* / Q000635:transmission / Q000821:virology; D002415:Cats; D004279:DNA, Viral / Q000235:genetics; D003627:Data Interpretation, Statistical; D016181:Feline Acquired Immunodeficiency Syndrome / Q000235:genetics / Q000276:immunology* / Q000821:virology; D059014:High-Throughput Nucleotide Sequencing / Q000379:methods*; D016089:Immunodeficiency Virus, Feline / Q000145:classification* / Q000235:genetics* / Q000472:pathogenicity; D015233:Models, Statistical
chemical_list: D004279:DNA, Viral