title: Improving HIV coreceptor usage prediction in the clinic using hints from next-generation sequencing data.
abstract: BACKGROUND
  Due to the high mutation rate of human immunodeficiency virus (HIV), drug-resistant-variants emerge frequently. Therefore, researchers are constantly searching for new ways to attack the virus. One new class of anti-HIV drugs is the class of coreceptor antagonists that block cell entry by occupying a coreceptor on CD4 cells. This type of drug just has an effect on the subset of HIVs that use the inhibited coreceptor. A good prediction of whether the viral population inside a patient is susceptible to the treatment is hence very important for therapy decisions and pre-requisite to administering the respective drug. The first prediction models were based on data from Sanger sequencing of the V3 loop of HIV. Recently, a method based on next-generation sequencing (NGS) data was introduced that predicts labels for each read separately and decides on the patient label through a percentage threshold for the resistant viral minority.
  
  
  RESULTS
  We model the prediction problem on the patient level taking the information of all reads from NGS data jointly into account. This enables us to improve prediction performance for NGS data, but we can also use the trained model to improve predictions based on Sanger sequencing data. Therefore, also laboratories without NGS capabilities can benefit from the improvements. Furthermore, we show which amino acids at which position are important for prediction success, giving clues on how the interaction mechanism between the V3 loop and the particular coreceptors might be influenced.
  
  
  BACKGROUND
  A webserver is available at http://coreceptor.bioinf.mpi-inf.mpg.de.
  
  
  BACKGROUND
  nico.pfeifer@mpi-inf.mpg.de.
authors.affiliation: Department of Computational Biology and Applied Algorithmics, Max Planck Institute for Informatics, Campus E1 4, 66123 Saarbrücken, Germany. nico.pfeifer@mpi-inf.mpg.de
authors.forename: Nico
authors.initials: N
authors.lastname: Pfeifer
authors.forename: Thomas
authors.initials: T
authors.lastname: Lengauer
mesh_terms: D019380:Anti-HIV Agents / Q000627:therapeutic use*; D015496:CD4-Positive T-Lymphocytes / Q000821:virology; D015658:HIV Infections / Q000188:drug therapy / Q000821:virology; D059014:High-Throughput Nucleotide Sequencing; D006801:Humans; D015728:Receptors, HIV / Q000037:antagonists & inhibitors*; D017422:Sequence Analysis, DNA; D020539:Sequence Analysis, Protein; D019562:Viral Load; D053586:Virus Internalization / Q000187:drug effects; D054299:env Gene Products, Human Immunodeficiency Virus / Q000737:chemistry* / Q000235:genetics
chemical_list: D019380:Anti-HIV Agents; D015728:Receptors, HIV; D054299:env Gene Products, Human Immunodeficiency Virus