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정상, Cancer SNP array 데이터에서 SCNA를 찾아주는 프로그램. GISTIC stands for Genomic Identification of Significant Targets in Cancer. Broad Institute에서 만듬. 2008년 버전 1 이후, 2011년 버전 2.0이 나옴.

Overall procedure

  1. Accurate definition of the copy number profile in each sample (from .CEL to segmented copy number profile)
  2. Identification/seperation of undering SCNAs - Deconstruction of segmented profile into underlying SCNAs. Allows for modelling of background rate of SCNAs and length-based separation of arm-level and focal SCNAs
  3. Scoring SCNAs in each region according to likelihood of occuring by chance
  4. Defining independent genomic regions undergoing significant levels of SCNA - Arbitrated pell-off algorithm
  5. Accurate definition of the copy number profile in each sample - RegBounder

Preprocessing for Genome-Wide Human SNP Array 6.0

  1. Make normalized copy number estimates (log2 ratios) from .CEL by GenePattern pipeline
  2. Segmentation using CBS (Circular Binary Segmentation) algorithm
  3. Median centering the segment values in each sample around 0. (여기까지의 데이터는 TCGA 사이트에서 "Level 3 segmented copy number data files"라는 이름으로 다운로드 가능 )
  4. Remove markers residing within previously annotated regions of germline copy number variation.
  5. Merge segments with fewer than 10 markers with the closest adjacent segment.

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