MinimumDistance

MinimumDistance is a software tool for detecting de novo copy number variants (CNVs) in case-parent trio studies. It addresses limitations of existing methods like the joint hidden Markov model (HMM) in PennCNV, which can produce false positives due to genomic waves and batch effects and is computationally intensive.

The key features of MinimumDistance are:

1. It exploits the trio design to use a univariate statistic called the minimum distance to reduce technical variation from probe effects and genomic waves.

2. It applies circular binary segmentation to segment the minimum distance and maximum a posteriori estimation to infer de novo CNVs from the segmented genome.

3. Compared to PennCNV on simulated data, MinimumDistance identifies fewer false positives on average and has comparable false negative rates.

4. It provides a nearly 8-fold speed increase compared to the joint HMM in PennCNV for analyzing case-parent trio data.