Autoencoders for genomic variation analysis

Table 1.

Compression factors of PCA versus VAE

Models Populations
Type |z| α European (EUR) East Asian (EAS) Native American (AMR) South Asian (SAS) African (AFR) Oceanian (OCE) West Asian (WAS)
PCA 2 ×0.41 ×0.38 ×0.42 ×0.39 ×0.33 ×0.36 ×0.38
VAE 10−4 ×0.68 ×0.64 ×0.76 ×0.62 ×0.53 ×0.50 ×0.67
10−5 ×0.65 ×0.61 ×0.73 ×0.60 ×0.52 ×0.49 ×0.63
PCA 4 ×0.41 ×0.37 ×0.41 ×0.38 ×0.33 ×0.36 ×0.38
VAE 10−4 ×0.77 ×0.69 ×0.87 ×0.68 ×0.56 ×0.58 ×0.71
10−5 ×0.73 ×0.69 ×0.81 ×0.66 ×0.54 ×0.63 ×0.68
PCA 8 ×0.41 ×0.37 ×0.41 ×0.38 ×0.33 ×0.36 ×0.37
VAE 10−4 ×1.00 ×0.93 ×1.17 ×0.88 ×0.63 ×0.68 ×0.89
10−5 ×0.96 ×0.90 ×1.08 ×0.88 ×0.63 ×0.74 ×0.88
PCA 16 ×0.40 ×0.36 ×0.41 ×0.38 ×0.32 ×0.35 ×0.37
VAE 10−4 ×1.59 ×1.39 ×1.73 ×1.32 ×0.84 ×1.01 ×1.37
10−5 ×1.25 ×1.12 ×1.35 ×1.04 ×0.70 ×0.90 ×1.08
PCA 32 ×0.39 ×0.36 ×0.40 ×0.37 ×0.32 ×0.34 ×0.36
VAE 10−4 ×2.00 ×1.75 ×2.33 ×1.69 ×1.03 ×1.27 ×1.72
10−5 ×1.67 ×1.45 ×1.85 ×1.39 ×1.85 ×1.23 ×1.28
PCA 64 ×0.37 ×0.34 ×0.38 ×0.35 ×0.31 ×0.33 ×0.34
VAE 10−4 ×2.04 ×1.82 ×2.27 ×1.75 ×1.16 ×1.47 ×1.82
10−5 ×1.69 ×1.54 ×1.96 ×1.47 ×0.96 ×1.30 ×1.49
PCA 128 ×0.34 ×0.32 ×0.35 ×0.32 ×0.29 ×0.30 ×0.32
VAE 10−4 ×1.54 ×1.45 ×1.61 ×1.41 ×1.06 ×1.25 ×1.43
10−5 ×1.47 ×1.37 ×1.56 ×1.35 ×0.97 ×1.20 ×1.37
PCA 256 ×0.30 ×0.28 ×0.30 ×0.28 ×0.25 ×0.27 ×0.28
VAE 10−4 ×0.97 ×0.93 ×1.00 ×0.93 ×0.79 ×0.86 ×0.93
10−5 ×0.94 ×0.90 ×0.97 ×0.89 ×0.73 ×0.84 ×0.90
PCA 512 ×0.24 ×0.23 ×0.24 ×0.23 ×0.21 ×0.22 ×0.23
VAE 10−4 ×0.54 ×0.53 ×0.55 ×0.53 ×0.48 ×0.50 ×0.53
10−5 ×0.53 ×0.52 ×0.54 ×0.51 ×0.45 ×0.49 ×0.52
  • The compression factors are computed as Formula using test data. A compression ratio of 1 corresponds to the identity, and values <1 and >1 correspond to compression and expansion, respectively. VAEs with a bottleneck of 32, 64, and 128 latent factors are capable of lossless compression of all human populations. Successful compression is marked in bold. |z| is the number of latent factors and α stands for learning rate.

This Article

  1. Genome Res. 36: 348-360

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