Advanced Options

These options allow changing of some advanced settings. The option –workdir is useful for avoiding writing out repetitive filenames in full, while consider using –maxiter, –maxtime or –quick-weights if you encounter problems when calculating weightings.
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All features allow you to add the option –workdir <directory> to specify the working directory. LDAK will then prefix any relative filenames with <directory>. This is especially useful when running on a cluster, when typically absolute filenames are required. For example, if provided with the command
ldak.out –calc-kins regions –file data –region 1 –weights /home/sections/weightsALL –work-dir /home
LDAK will look for the datafiles /home/data.ped and /home/data.map, and will write results to /home/regions. By contrast, becadvanced-options/ause /home/sections/weightsALL is an absolute filename, this will not be prefixed by the working directory.

Note, if running on a Mac, this option becomes mandatory, so even if using relative filenames, add to your command line
–workdir ./
(telling LDAK to prefix names by the current directory).
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–section-length <num_of_predictors> and –buffer <num_of_predictors> – changes the target section length and size of buffer region to use at the ends of each section.  We used to suggest increasing these for more dense SNP arrays, but now we suggest calculating weightings a second time instead.
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–maxiter <float> (default 100,000) – the maximum number of iterations used in the simplex method. Consider changing this if calculating weights fails with the error message “did not finish within X iterations”.
–maxtime <float> (default 1200) – the maximum time (in minutes) used in the simplex method. Consider changing this if calculating weights fails with the error message “did not finish within X minutes”.

–quick-weights <YES/NO> (default NO) – by default, LDAK will estimate weightings using a linear/quadratic solver. When –quick-weights YES is supplied, LDAK will instead report weightings equal to 1/l_j, where l_j indicates the total duplication of SNP j (i.e., one plus the sum of correlation squares with neighbouring SNPs). This approach guarantees to find a set of weightings, but these weightings will only be approximate, so this option should generally be used only when the standard approach fails.