Dataset Open Access

HaMMLET - Supplemental Material

Wiedenhoeft, John; Brugel, Eric; Schliep, Alexander

HaMMLET is a novel type of Bayesian Hidden Markov Model, using dynamically adaptive wavelet compression for improved speedup and convergence behaviour of Forward-Backward Gibbs sampling.

This data set contains supplemental material for HaMMLET's initial publication.

Files (27.1 GB)
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checksums.md5
md5:11a4056e855a3c2ba4b61f5eff9c91c1
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S1_Figures_Breakpoint_Detection_and_Merging.zip
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S2_Figures_Spatial_Resolution_Study.zip
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S3_Figures_Testing.zip
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S4_Figures_GSE23949.zip
md5:c83ef8436ca78bd6893754219f5fb004
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S5_Figure_Maximum_Compression.tiff
md5:2b966599dc7369f85f459cd667862fe6
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S6_Dataset_Simulations_Speed_Convergence.tar.gz.00
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S6_Dataset_Simulations_Speed_Convergence.tar.gz.08
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S6_Dataset_Simulations_Speed_Convergence.tar.gz.09
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S6_Dataset_Simulations_Speed_Convergence.tar.gz.10
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S6_Dataset_Simulations_Speed_Convergence.tar.gz.11
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S6_Dataset_Simulations_Speed_Convergence.tar.gz.12
md5:3063e21dc444fb3632be8aab93f0a69c
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S7_Figures_Coriell_ATCC_BRC.zip
md5:522586990bcf4a2c46770b05e4b7a293
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