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Table 1 Computational cost of both MBD implementations

From: DepthTools: an R package for a robust analysis of gene expression data

 

Computational cost

 

Dataset size

Nested implementation. Time (s)

Matrix reordering. Time (s)

10 × 500

0.1663

0.0151

25 × 500

1.1386

0.0148

10 × 1000

0.3570

0.0318

25 × 1000

2.2870

0.0277

  1. Average time needed to compute the MBD of a sample of dimension 500 or 1000 with respect to a dataset with 10 or 25 samples (of the corresponding dimension), using the nested for loop implementation of the depth and the implementation based on reordering the columns of the dataset.