Base File: --a1 Column header containing allele 1 (effective allele) Default: A1 --a2 Column header containing allele 2 (non-effective allele) Default: A2 --base | -b Base association file --base-info Base INFO score filtering. Format should be <Column name>:<Threshold>. SNPs with info score less than <Threshold> will be ignored Column name default: INFO Threshold default: 0.9 --base-maf Base MAF filtering. Format should be <Column name>:<Threshold>. SNPs with maf less than <Threshold> will be ignored. An additional column can also be added(e.g. also filter MAF for cases), using the following format: <Column name>:<Threshold>,<Column name>:<Threshold> --beta Whether the test statistic is in the form of BETA or OR. If set, test statistic is assume to be in the form of BETA. Mutually exclusive from --or --bp Column header containing the SNP coordinate Default: BP --chr Column header containing the chromosome Default: CHR --index If set, assume the INDEX instead of NAME for the corresponding columns are provided. Index should be 0-based(start counting from 0) --no-default Remove all default options. If set, PRSice will notset any default column name and you must manually provide all required columns (--snp, --stat, --A1, --pvalue) --or Whether the test statistic is in the form of BETA or OR. If set, test statistic is assume to be in the form of OR. Mutually exclusive from --beta --pvalue | -p Column header containing the p-value Default: P --snp Column header containing the SNP ID Default: SNP --stat Column header containing the summary statistic If --beta is set, default as BETA. Otherwise, will search for OR or BETA from the header of the base file
Target File: --binary-target Indicate whether the target phenotype is binary ornot. Either T or F should be provided where T represent a binary phenotype. For multiple phenotypes, the input should be separated by comma without space. Default: T if --beta and F if --beta is not --geno Filter SNPs based on gentype missingness --info Filter SNPs based on info score. Only used for imputed target --keep File containing the sample(s) to be extracted from the target file. First column should be FID and the second column should be IID. If --ignore-fid is set, first column should be IID Mutually exclusive from --remove --maf Filter SNPs based on minor allele frequency(MAF) --nonfounders Keep the nonfounders in the analysis Note: They will still be excluded from LD calculation --pheno | -f Phenotype file containing the phenotype(s). First column must be FID of the samples and the second column must be IID of the samples. When --ignore-fid is set, first column must be the IID of the samples. Must contain a header if --pheno-col is specified --pheno-col | -F Headers of phenotypes to be included from the phenotype file --prevalence | -k Prevalence of all binary trait. If provided will adjust the ascertainment bias of the R2. Note that when multiple binary trait is found, prevalence information must be provided for all of them --remove File containing the sample(s) to be removed from the target file. First column should be FID and the second column should be IID. If --ignore-fid is set, first column should be IID Mutually exclusive from --keep --target | -t Target genotype file. Currently support both BGEN and binary PLINK format. For multiple chromosome input, simply substitute the chromosome number with #. PRSice will automatically replace # with 1-22 For binary plink format, you can also specify a seperate fam file by <prefix>,<fam file> --target-list File containing prefix of target genotype files. Similar to --target but allow more flexibility. Do not support external fam file at the moment --type File type of the target file. Support bed (binary plink)and bgen format. Default: bed
Dosage: --allow-inter Allow the generate of intermediate file. This will speed up PRSice when using dosage data as clumping reference andfor hard coding PRS calculation --dose-thres Translate any SNPs with highest genotype probability less than this threshold to missing call --hard-thres A hardcall is saved when the distance to the nearest hardcall is less than the hardcall threshold. Otherwise a missing code is saved Default is: 0.1 --hard Use hard coding instead of dosage for PRS construction. Default is to use dosage instead of hard coding
Clumping: --clump-kb The distance for clumping in kb Default: 250 --clump-r2 The R2 threshold for clumping Default: 0.1 (1mb for PRSet) --clump-p The p-value threshold use for clumping. Default: 1 --ld | -L LD reference file. Use for LD calculation. If not provided, will use the post-filtered target genotype for LD calculation. Support multiple chromosome input Please see --target for more information --ld-dose-thres Translate any SNPs with highest genotype probability less than this threshold to missing call --ld-geno Filter SNPs based on genotype missingness --ld-hard-thres A hardcall is saved when the distance to the nearest hardcall is less than the hardcall threshold. Otherwise a missing code is saved Default is: 0.1 --ld-info Filter SNPs based on info score. Only used for imputed LD reference --ld-keep File containing the sample(s) to be extracted from the LD reference file. First column should be FID and the second column should be IID. If --ignore-fid is set, first column should be IID Mutually exclusive from --ld-remove No effect if --ld was not provided --ld-list File containing prefix of LD reference files. Similar to --ld but allow more flexibility. Do not support external fam file at the moment --ld-maf Filter SNPs based on minor allele frequency --ld-remove File containing the sample(s) to be removed from the LD reference file. First column should be FID and the second column should be IID. If --ignore-fid is set, first column should be IID Mutually exclusive from --ld-keep --ld-type File type of the LD file. Support bed(binary plink) and bgen format. Default: bed --no-clump Stop PRSice from performing clumping --proxy Proxy threshold for index SNP to be considered as part of the region represented by the clumped SNP(s). e.g. --proxy 0.8 means the index SNP will represent region of any clumped SNP(s) that has a R2>=0.8 even if the index SNP does not physically locate within the region
Covariate: --cov | -C Covariate file. First column should be FID and the second column should be IID. If --ignore-fid is set, first column should be IID --cov-col | -c Header of covariates. If not provided, will use all variables in the covariate file. By adding @ in front of the string, any numbers within [ and ] will be parsed. E.g. @PC[1-3] will be read as PC1,PC2,PC3. Discontinuous input are also supported: @cov[1.3-5] will be parsed as cov1,cov3,cov4,cov5 --cov-factor Header of categorical covariate(s). Dummy variable will be automatically generated. Any items in --cov-factor must also be found in --cov-col Also accept continuous input(start with @).
P-value Thresholding: --bar-levels Level of barchart to be plotted. When --fastscore is set, PRSice will only calculate the PRS for threshold within the bar level. Levels should be comma separated without space --fastscore Only calculate threshold stated in --bar-levels --no-full By default, PRSice will include the full model, i.e. p-value threshold = 1. Setting this flag will disable that behaviour --interval | -i The step size of the threshold. Default: 5e-05 --lower | -l The starting p-value threshold. Default: 5e-08 --model Genetic model use for regression. The genetic encoding is based on the base data where the encoding represent number of the coding allele Available models include: add - Additive model, code as 0/1/2 (default) dom - Dominant model, code as 0/1/1 rec - Recessive model, code as 0/0/1 het - Heterozygous only model, code as 0/1/0 --missing Method to handle missing genotypes. By default, final scores are averages of valid per-allele scores with missing genotypes contribute an amount proportional to imputed allele frequency. To throw out missing observations instead(decreasing the denominator in the final average when this happens), use the 'SET_ZERO' modifier. Alternatively, you can use the 'CENTER' modifier to shift all scores to mean zero. --no-regress Do not perform the regression analysis and simply output all PRS. --score Method to calculate the polygenic score. Available methods include: avg - Take the average effect size(default) std - Standardize the effect size con-std - Standardize the effect size using mean and sd derived from control samples sum - Direct summation of the effect size --upper | -u The final p-value threshold. Default: 0.5
PRSet: --background String to indicate a background file. This string should have the format of Name:Type where type can be bed - 0-based range with 3 column. Chr Start End range - 1-based range with 3 column. Chr Start End gene - A file contain a column of gene name --bed | -B Bed file containing the selected regions. Name of bed file will be used as the region identifier. WARNING: Bed file is 0-based --feature Feature(s) to be included from the gtf file. Default: exon,CDS,gene,protein_coding. --full-back Use the whole genome as background for competitive p-value calculation --gtf | -g GTF file containing gene boundaries. Required when --msigdb is used --msigdb | -m MSIGDB file containing the pathway information. Require the gtf file --snp-set Provide a SNP set file containing the snp set(s). Two different file format is allowed: SNP list format - A file containing a single column of SNP ID. Name of the set will be the file name or can be provided using --snp-set File:Name MSigDB format - Each row represent a single SNP set with the first column containing the name of the SNP set. --wind-3 Add N base(s) to the 3' region of each feature(s) --wind-5 Add N base(s) to the 5' region of each feature(s)
Misc: --all-score Output PRS for ALL threshold. WARNING: This will generate a huge file --chr-id Try to construct an RS ID for SNP based on its chromosome, coordinate, effective allele and non-effective allele. e.g. c:L-aBd is translated to: <chr>:<coordinate>-<effective><noneffective>d This is always truefor target file, whereas for base file, this is only used if the RS ID wasn't provided --exclude File contains SNPs to be excluded from the analysis --extract File contains SNPs to be included in the analysis --id-delim This parameter causes sample IDs to be parsed as <FID><delimiter><IID>; the default delimiter is '_'. --ignore-fid Ignore FID for all input. When this is set, first column of all file will be assume to be IID instead of FID --keep-ambig Keep ambiguous SNPs. Only use this option if you are certain that the base and target has the same A1 and A2 alleles --logit-perm When performing permutation, still use logistic regression instead of linear regression. This will substantially slow down PRSice --memory Maximum memory usage allowed(in Mb). PRSice will try its best to honor this setting --non-cumulate Calculate non-cumulative PRS. PRS will be reset to 0 for each new P-value threshold instead of adding up --out | -o Prefix for all file output --perm Number of permutation to perform. This swill generate the empirical p-value. Recommend to use value larger than 10,000 --print-snp Print all SNPs that remains in the analysis after clumping is performed. For PRSet, Y indicate the SNPs falls within the gene set of interest and N otherwise. If only PRSice is performed, a single "gene set" called "Base" will be presented with all entries marked as Y --seed | -s Seed used for permutation. If not provided, system time will be used as seed. When same seed and same input is provided, same result can be generated --thread | -n Number of thread use --use-ref-maf When specified, missingness imputation will be performed based on the reference samples --ultra Ultra aggressive memory usage. When this is enabled PRSice and PRSet will try to load all genotypes into memory after clumping is performed. This should drastically speed up PRSice and PRSet at the expense of higher memory consumption. Has no effect for dosage score --x-range Range of SNPs to be excluded from the whole analysis. It can either be a single bed file or a comma seperated list of range. Range must be in the format of chr:start-end or chr:coordinate --help | -h Display this help message
Please provide the required parameters
5. 二分類性狀計算
5.1 運行代碼
代碼：
Rscript PRSice.R --dir . --prsice ./PRSice_linux --base TOY_BASE_GWAS.assoc --target TOY_TARGET_DATA --thread 1 --stat OR --binary-target T
Base file: TOY_BASE_GWAS.assoc Header of file is: SNP CHR BP A1 A2 P OR
Reading 100.00% 91062 variant(s) observed in base file, with: 2226 variant(s) located on haploid chromosome 88836 total variant(s) included from base file
Loading Genotype info from target ==================================================
2000 people (1024 male(s), 976 female(s)) observed 2000 founder(s) included
Warning: Currently not support haploid chromosome and sex chromosomes
88836 variant(s) included
There are a total of 1 phenotype to process
Start performing clumping
Clumping Progress: 100.00% Number of variant(s) after clumping : 88836
Processing the 1 th phenotype
Phenotype is a binary phenotype 1000 control(s) 1000case(s)
Start Processing Processing 100.00% There are 1 region(s) with p-value less than 1e-5. Please note that these results are inflated due to the overfitting inherent in finding the best-fit PRS (but it's still best to find the best-fit PRS!). You can use the --perm option (see manual) to calculate an empirical P-value.
Begin plotting Current Rscript version = 2.3.3 Plotting Bar Plot Plotting the high resolution plot
Pheno Set Threshold R2 P Coefficient Standard.Error Num_SNP - Base 0.000250050.01336968.43169e-06-0.1972660.04429032 - Base 0.000300050.008244730.000456434-0.2252040.06425033 - Base 0.000400050.00897250.000256089-0.3502670.09580355 - Base 0.000450050.01013390.000102845-0.4454970.1147076 - Base 0.000650050.005329750.004775-0.4020030.1424628 - Base 0.000700050.008766540.00030122-0.5492460.1519679 - Base 0.000800050.002336070.061455-0.3692190.19742213 - Base 0.000850050.001531570.129826-0.3429230.22638415 - Base 0.000950050.0001243240.665873-0.1007250.23325816
head PRSice.summary Phenotype Set Threshold PRS.R2 Full.R2 Null.R2 Prevalence Coefficient Standard.Error P Num_SNP - Base 0.44630.05200820.05200820 - 86.2889.963314.69368e-1836759
Base file: TOY_BASE_GWAS.assoc Header of file is: SNP CHR BP A1 A2 P OR
Reading 100.00% 91062 variant(s) observed in base file, with: 2226 variant(s) located on haploid chromosome 88836 total variant(s) included from base file
Loading Genotype info from target ==================================================
2000 people (1024 male(s), 976 female(s)) observed 2000 founder(s) included
Warning: Currently not support haploid chromosome and sex chromosomes
88836 variant(s) included
There are a total of 1 phenotype to process
Start performing clumping
Clumping Progress: 100.00% Number of variant(s) after clumping : 88836
Processing the 1 th phenotype
Phenotype is a binary phenotype 1000 control(s) 1000case(s)
Start Processing Processing 100.00% There are 1 region(s) with p-value between 0.1and1e-5 (may not be significant).
Begin plotting Current Rscript version = 2.3.3 Plotting Bar Plot Plotting the high resolution plot
Pheno Set Threshold R2 P Coefficient Standard.Error Num_SNP - Base 0.000250050.008454760.000387368-0.00163710.0004613432 - Base 0.000300050.008316820.000432057-0.002435450.000691953 - Base 0.000400050.008825260.000289046-0.004180920.001153385 - Base 0.000450050.008812190.000292041-0.005013470.001384076 - Base 0.000650050.008365540.00041563-0.006506310.001843178 - Base 0.000700050.008363930.000416159-0.007318890.002073579 - Base 0.000800050.008304430.000436251-0.01053460.0029952313 - Base 0.000850050.008287420.00044217-0.01214230.0034558415 - Base 0.000950050.007639540.000739963-0.01246030.0036926716
「測試數(shù)據(jù)：」
「注意，上面數(shù)據(jù)如果無法下載，可以公眾號（育種數(shù)據(jù)分析之放飛自我）后臺回復(fù)PRS，獲得軟件包和測試數(shù)據(jù)?！?/strong>
