Perform genome-wide association analysis using a linear model
pacoxph [ command-line options ]
pacoxph runs a linear regression on large imputed data sets in an efficient way.
-p, -\^-pheno FILE
Read phenotype data from FILE
-i, -\^-info FILE
Read SNP information from FILE (e.g. MLINFO file).
-d, -\^-dose FILE
SNP predictor (e.g. MLDOSE/MLPROB) file name.
-m, -\^-map FILE
Map file name, containing base pair positions for each SNP.
-n, -\^-nids NUMBER
Number of people to analyse.
-c, -\^-chrom FILE
Chromosome (to be passed to output).
-o, -\^-out FILE
Output file name (default is regression.out.txt ).
-s, -\^-skipd NUMBER
How many columns to skip in predictor (dose/prob) file (default is 2).
-t, -\^-ntraits NUMBER
How many traits are analysed (default is 2).
-g, -\^-ngpreds NUMBER
How many predictor columns per marker (default 1 = MLDOSE; else use 2 for MLPROB).
-a, -\^-separat FILE
Character to separate fields (default is space).
-r, -\^-score
Use the score test.
-e, -\^-no-head
Do not report header line in the output.
-l -\^-allcov
Report estimates for all covariates (large outputs!).
-b, -\^-interaction
Which covariate to use for interaction with SNP analysis (default is no interaction, 0).
-k, -\^-interaction_only
Like -\^-interaction but without covariate acting in interaction with SNP (default is no interaction, 0).
-\^-help
Print help.
The bugtracker is located at
https://r-forge.r-project.org/tracker/?group_id=505
Lennart C. Karssen