100 Line 1: 250 Line 2: 100 Line 3: 3 40 TestSNPSimuPos.dat Line 4: 5 TestBT.dat TestBlockRes-005.dat Line 5: 1 0.80 0.0499 Line 6: 4 0.80 0.0499 Line 7: 2 TestPreSNP.dat Line 8: 1 1 1 TestSNPName.dat Line 9: 2 TestHapPat-004.dat Line 10: 2 100 TestPermute-004.dat Line 11: Explaination for each line in this file: Line 1: MaxNumSample one parameter, the maximum number of samples (haplotypes or individuals), must be positive; Line 2: MaxNumMarker one parameter, the maximum length of haplotypes (alternatively, the number of markers), must be positive; Line 3: MaxBlockLen one parameter, the maximum length that a haplotype block can be extended, must be positive; Line 4: dynamicID [reqGenomeCoverage][reqNumTagSNP][mapFile] up to three parameters, at least one parameter, the different dynamic programming algorithms; dynamicID: 1. Dynamic Programming algorithm to find the minimum number of tag SNPs; 2. Parametric dynamic Programming algorithm; 3. two-way discrete dynamic algorithm; If dynamicID==2, the second parameter is the fraction of genome that you want to cover (greater than 0 less than 1). The third parameter is the file containing position of SNPs. If dynamicID==3, the second parameter is the number of tag SNPs that you want to genotyped to cover (greater than 0 less than 1). The third parameter is the file containing position of SNPs. Line 5: dataID dataFile statOutFile three parameters, the different kinds of input data; dataID: 1. the haplotype data; 2. the genotype data from unrelated indivduals, the most-likely haplotype pairs identified from the EM algorithm will be used in block partitioning; 3. the genotype data from unrelated indivduals, the haplotype and their frequencies estimated from the EM algorithm will be used in block partitioning; 4. the genotype data from a general pedigree, the haplotype and their frequencies estimated from the EM algorithm will be used in block partitioning; 5. the block and the number of tag SNPs obtained by other program; dataFile: the file of input data; statOutFile: the file of output data; Line 6: blockID [blockPercent][ldLowerBound][ldFraThreshold][comHapThreBlock] up to three parameters, the different methods for block partitioning; blockID: 1. The common haplotypes account for majority of obserevd haplotypes; [blockPercent]: the minimum percentage of common haplotypes in a block; [comHapThreBlock]: the threshold for common haplotypes in block partitioning; 2. The Empirical LD method. The fraction of strong pair-wise LD D' must be greater than a threshold; [ldLowerBound]: for defining strong LD; [ldFraThreshold]: 3. The Four-Gamete Test. Suggest to use when the haplotype are available. [comHapThreBlock]: the threshold for common haplotypes in block partitioning. In this case, we must be careful to use it. We suggest setting it as 0 when using haplotype data. Line 7: tagMethodID [coverPercent][comHapThreTag][addSNPNum] up to three parameters, the different methods for tag SNP selection. atgMethodID: 1. Distinguish the common haplotypes account for a percentage haplotypes; only effective for blockID==1. [coverPercent]: the percentage of ditinguished common haplotypes, less than blockPercent; [comHapThreTag]: the threshold for common haplotypes in tag SNP Selection, less than comHapThreBlock; 2. Distinguish all common haplotypes. [comHapThreTag]: the threshold for common haplotypes in tag SNP Slection; 3. Haplotype Diversity. [coverPercent]: the faction of overall haplotype diversity explained by tag SNPs; [comHapThreTag]: the threshold for common haplotypes in tag SNP Slection; 4. Haplotype Entropy: [coverPercent]: the faction of overall haplotype entropy explained by tag SNPs; [comHapThreTag]: the threshold for common haplotypes in tag SNP Slection; 5. Haplotype Prediction Strenth: [coverPercent]: the minimum of prediction strength among all common haplotypes; [comHapThreTag]: the threshold for common haplotypes in tag SNP Selection; 6. Minimum R-Square: [coverPercent]: the minimum measure of r^2 between non-tag SNPs and tag SNPs; [comHapThreTag]: the threshold for common haplotypes in tag SNP Slection; 7. Distinguish all common haplotypes in the presence of missing SNPs. [comHapThreTag]: the threshold for common haplotypes in tag SNP Selection; [addSNPNum]: the number of missing SNPs allowed in the analysis. 8. Always 1. It can be used to find partition blocks with minimum number of blocks Line 8: preTagMethod [preTagFile] up to parameters, if you have pre-selected tag SNPs; preTagMethod: 1. You have the a set of pre-selected tag SNPs; [preTagFile]: the file contains the pre-selected tag SNPs; 2. You do not have the a set of pre-selected tag SNPs; Line 9: outInterResFlag outTagSNPFlag [SNPNameFlag][SNPNameFile] two parameters, control the format of output. outInterResFlag: 1. Output all possible blocks and tag SNPs for further use; 2. Do not output all possible blocks and tag SNPs; outTagSNPFlag: 1. Output tag SNPs for each block; 2. Do not output tag SNPs; [SNPNameFlag]: 1. The name of SNPs provided from SNPNameFile is used to label tag SNPs; 2. The index of SNPs is used to label tag SNPs; [SNPNameFile]: the file that contains the name of SNPs; Line 10:patFlag [patOutFile] up to two paramteres, if you want to output haplotype patterns for each block; patFlag: 1. Output the haplotype patterns for each block to [patOutFile]; 2. Do not output the haplotype patterns Line 11:permuteFlag [permuteNum][permuteOutFile] up tp three parameters, if we do permutation test when dataID==3,4,5 and dynamicID=1 permuteFlag: 1. Do permutation test. 2. Do not do permutation test.