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README-filterHD.md

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filterHD command line arguments

Typical usage options

  • --data [file] Input data.

    The file format is the same as in cloneHD for --cna, --baf or --snv (see here). Multiple samples are processed independently, one by one.

  • --mode [1/2/3/4] Emission modes.

    1. Binomial (for SNV data and BAF data (use with --reflect 1))
    2. Beta-Binomial (over-dispersed Binomial) 3: Poisson (for read depth data) 4: Negative-Binomial (over-dispersed Poisson)
In modes 3/4, the range of the hidden emission rate is learned
automatically. For modes 1/2, it is always in [0,1]. Reflective
boundary conditions are used.

  • --pre [string:"./out"] Prefix for all output files.

  • --dist [0/1:0] Whether to print also the posterior distribution.

    The posterior mean, std-dev and jump probability are always printed to files pre.posterior-[int].txt, one for each sample in the input. With 1, the whole posterior distribution is also printed, so files can be big.

  • --jumps [0/1:0] Whether to print posterior jump probability.

    The posterior jump probability is compounded over all samples. It can be used with --min-jump [double] below, to consolidate jumps.

  • --reflect [0/1:0] If 1, binomial observations n in N and (N-n) in N are assumed to be identical. Use this option for BAF data.

Parameter options

The continuous state space HMM underlying filterHD is determined by the following global parameters. They can all be fixed, otherwise they are learned from the data.

  • --jump [double] Fix the jump probability per length unit (bp).
  • --sigma [double] Fix the diffusion constant.
  • --shape [double] Fix the shape parameter for modes 2/4. If >1000, use modes 1/3.
  • --rnd [double] Fix the rate of random emissions.

For all of the above parameters, initial values for the numerical optimization can be given. This might be useful if you suspect several local optima and want to start in the neighbourhood of a particular one.

  • --jumpi [double]
  • --sigmai [double]
  • --shapei [double]
  • --rndi [double]

Further advanced options

  • --min-jump [double:0.0] Consolidate jumps down to --min-jump.

    The posterior jump probability track will be consolidated by merging neighboring jump events into unique jumps, down to the minimum value given here. Can only be used together with --jumps 1.

  • --filter-pVal [0/1:0] Use p-Value filter.

    Filter sites where the p-Value of the observation is below 10/nSites, where nSites is the total number of sites in a sample.

  • --filter-shortSeg [int:0] Use short-segment filter.

    Filter sites within short segments between jumps. All filtered data will be in the file ending pre.filtered.txt, which will be in the same format as the input file.

  • --grid [int:100] Set the grid size.

    The grid size for the internal representation of continuous distributions. For large ranges in mode 3/4, it can make sense to increase this resolution.

filterHD output

filterHD generates a few output files automatically. Here, we provide annotated screenshots for them for the simulated example data set.

STDOUT

stdout

Output file

posterior1

The posterior mean value of the hidden emission rate and jump probabilities

posterior2

The same as above, but here a bias (normal) was used, so the rate is scaled accordingly. Note: in filterHD, the bias field is not scaled to have mean 1!

posterior3

The same as above, but here the whole posterior distribution was requested with --dist 1