title: Clonality: an R package for testing clonal relatedness of two tumors from the same patient based on their genomic profiles.
abstract: CONCLUSIONS
  If a cancer patient develops multiple tumors, it is sometimes impossible to determine whether these tumors are independent or clonal based solely on pathological characteristics. Investigators have studied how to improve this diagnostic challenge by comparing the presence of loss of heterozygosity (LOH) at selected genetic locations of tumor samples, or by comparing genomewide copy number array profiles. We have previously developed statistical methodology to compare such genomic profiles for an evidence of clonality. We assembled the software for these tests in a new R package called 'Clonality'. For LOH profiles, the package contains significance tests. The analysis of copy number profiles includes a likelihood ratio statistic and reference distribution, as well as an option to produce various plots that summarize the results.
  
  
  BACKGROUND
  Bioconductor (http://bioconductor.org/packages/release/bioc/html/Clonality.html) and http://www.mskcc.org/mskcc/html/13287.cfm.
authors.affiliation: Department of Epidemiology and Biostatistics, Memorial Sloan-Kettering Cancer Center, New York, NY 10065, USA. ostrovni@mskcc.org
authors.forename: Irina
authors.initials: I
authors.lastname: Ostrovnaya
authors.forename: Venkatraman E
authors.initials: VE
authors.lastname: Seshan
authors.forename: Adam B
authors.initials: AB
authors.lastname: Olshen
authors.forename: Colin B
authors.initials: CB
authors.lastname: Begg
mesh_terms: D002999:Clone Cells; D023281:Genomics; D006801:Humans; D019656:Loss of Heterozygosity; D009369:Neoplasms / Q000235:genetics*; D020411:Oligonucleotide Array Sequence Analysis; D012984:Software