Shifting Level Models Segmentation

The Shifting Level Models (SLM) segmentation mode follows from the R implementation of SLMSuite: a suite of algorithms for segmenting genomic profiles.

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--cnv-slm-eta—Baseline probability that the mean process changes its value. The default is 1e-5.

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--cnv-slm-fw—Minimum number of data points for a CNV to be emitted. The default is 0, which means segments with one design probe could in effect be emitted.

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--cnv-slm-omega—Scaling parameter modulating relative weight between experimental/biological variance. The default is 0.3.

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--cnv-slm-stepeta—Distance normalization parameter. The default is 10000. This option is only valid for HSLM.

Regardless of the segmentation method, initial segments are split across large gaps where depth data is unavailable, such as across centromeres.