Skip to main content

Table 1 Performance comparison of different integrative analyses on simulated datasets. The average of each metric was presented and the standard deviation was not shown because the metric values are very stable between different numerical repeats

From: Integrating heterogeneous genomic data to accurately identify disease subtypes

Scale issue

Data1

Data2

Concatenation

SNF

iBFE1

iBFE2

iBFE2

PCCintraclass

0.023 ± 0.0011

0.025 ± 0.0019

0.031 ± 0.0034

0.17 ± 0.0067

0.30 ± 0.012

0.23 ± 0.014

0.28 ± 0.015

PCCinterclass

−0.0018 ± 0.00021

−0.0067 ± 0.00033

0.0068 ± 0.00035

0.15 ± 0.0054

−0.30 ± 0.013

−0.21 ± 0.015

−0.26 ± 0.015

PCCintraclass-PCCinterclass

0.024 ± 0.0014

0.031 ± 0.0020

0.024 ± 0.0035

0.021 ± 0.012

0.60 ± 0.022

0.44 ± 0.024

0.54 ± 0.025

Simintraclass

0.02 ± 0.0023

0.02 ± 0.0022

0.02 ± 0.0023

0.97 ± 0.004

0.32 ± 0.011

0.23 ± 0.012

0.29 ± 0.010

Siminterclass

0 ± 0.0

0 ± 0.0

0 ± 0.0

0.97 ± 0.005

0.22 ± 0.012

0.17 ± 0.013

0.22 ± 0.013

Simintraclass-Siminterclass

0.02 ± 0.0023

0.02 ± 0.0022

0.02 ± 0.0023

0.00057 ± 0.0011

0.10 ± 0.022

0.06 ± 0.025

0.07 ± 0.023

ACC_rfLOO

0.59 ± 0.057

0.95 ± 0.032

0.94 ± 0.045

0.52 ± 0.062

0.99 ± 0.035

0.99 ± 0.036

0.99 ± 0.036

NMI_kmeans

0.035 ± 0.0085

0.035 ± 0.0089

0.035 ± 0.0093

0.0052 ± 0.0012

0.93 ± 0.054

0.92 ± 0.051

0.93 ± 0.055

Noise type

PCCintraclass

0.025 ± 0.0031

0.066 ± 0.0022

0.13 ± 0.014

0.013 ± 0.0029

0.32 ± 0.034

0.23 ± 0.030

0.31 ± 0.031

PCCinterclass

−0.0040 ± 0.00097

−0.049 ± 0.0012

0.097 ± 0.0023

−0.011 ± 0.0058

−0.32 ± 0.031

−0.22 ± 0.029

−0.29 ± 0.033

PCCintraclass-PCCinterclass

0.029 ± 0.0032

0.12 ± 0.0024

0.033 ± 0.016

0.024 ± 0.0067

0.64 ± 0.061

0.45 ± 0.059

0.60 ± 0.063

Simintraclass

0.02 ± 0.0023

0.02 ± 0.0025

0.02 ± 0.0026

0.99 ± 0.0007

0.27 ± 0.012

0.25 ± 0.015

0.28 ± 0.013

Siminterclass

0 ± 0.0

0 ± 0.0

0 ± 0.0

0.99 ± 0.0014

0.16 ± 0.009

0.15 ± 0.011

0.16 ± 0.011

Simintraclass-Siminterclass

0.02 ± 0.0023

0.02 ± 0.0025

0.02 ± 0.0026

0.00021 ± 0.0020

0.11 ± 0.020

0.10 ± 0.026

0.12 ± 0.023

ACC_rfLOO

0.54 ± 0.023

0.98 ± 0.015

0.97 ± 0.021

0.93 ± 0.013

0.96 ± 0.015

0.95 ± 0.016

0.96 ± 0.018

NMI_kmeans

0.015 ± 0.0021

0.82 ± 0.0023

0.024 ± 0.0033

0.0042 ± 0.00056

0.83 ± 0.017

0.82 ± 0.018

0.82 ± 0.015

Noise size

PCCintraclass

0.023 ± 0.0031

0.048 ± 0.0015

0.026 ± 0.0033

0.0070 ± 0.00067

0.13 ± 0.038

0.09 ± 0.023

0.11 ± 0.031

PCCinterclass

−0.0041 ± 0.00009

−0.028 ± 0.0012

−0.0071 ± 0.00013

−0.0045 ± 0.00021

−0.13 ± 0.037

−0.08 ± 0.025

−0.10 ± 0.033

PCCintraclass-PCCinterclass

0.027 ± 0.0031

0.076 ± 0.0024

0.033 ± 0.0034

0.012 ± 0.00069

0.26 ± 0.065

0.17 ± 0.049

0.21 ± 0.061

Simintraclass

0.02 ± 0.0014

0.02 ± 0.0011

0.02 ± 0.0015

0.99 ± 0.00002

0.26 ± 0.015

0.19 ± 0.016

0.23 ± 0.017

Siminterclass

0 ± 0.0

0 ± 0.0

0 ± 0.0

0.99 ± 0.00003

0.20 ± 0.017

0.16 ± 0.016

0.18 ± 0.018

Simintraclass-Siminterclass

0.02 ± 0.0014

0.02 ± 0.0011

0.02 ± 0.0015

0.00016 ± 0.0006

0.06 ± 0.027

0.03 ± 0.030

0.05 ± 0.033

ACC_rfLOO

0.59 ± 0.051

0.84 ± 0.034

0.82 ± 0.054

0.86 ± 0.041

0.91 ± 0.052

0.90 ± 0.053

0.91 ± 0.055

NMI_kmeans

0.024 ± 0.0081

0.58 ± 0.043

0.028 ± 0.0097

0.0019 ± 0.00091

0.56 ± 0.062

0.55 ± 0.055

0.57 ± 0.063

Partial clustering

PCCintraclass

0.049 ± 0.0038

0.046 ± 0.0042

0.06 ± 0.0021

0.027 ± 0.0023

0.13 ± 0.05

0.10 ± 0.04

0.12 ± 0.06

PCCinterclass

0.0010 ± 0.00085

−0.0011 ± 0.00092

−0.016 ± 0.0034

−0.025 ± 0.0026

−0.11 ± 0.023

−0.10 ± 0.024

−0.12 ± 0.025

PCCintraclass-PCCinterclass

0.048 ± 0.0043

0.048 ± 0.0047

0.079 ± 0.0070

0.053 ± 0.0049

0.24 ± 0.067

0.20 ± 0.062

0.24 ± 0.073

Simintraclass

0.02 ± 0.0041

0.02 ± 0.0044

0.02 ± 0.0063

0.99 ± 0.00011

0.27 ± 0.019

0.23 ± 0.020

0.25 ± 0.022

Siminterclass

0 ± 0.0

0 ± 0.0

0 ± 0.0

0.99 ± 0.00012

0.21 ± 0.021

0.18 ± 0.021

0.20 ± 0.021

Simintraclass-Siminterclass

0.02 ± 0.0041

0.02 ± 0.0044

0.02 ± 0.0063

0.00040 ± 0.00022

0.061 ± 0.033

0.052 ± 0.035

0.057 ± 0.038

ACC_rfLOO

0.86 ± 0.028

0.87 ± 0.026

0.93 ± 0.016

0.96 ± 0.029

0.90 ± 0.023

0.89 ± 0.031

0.91 ± 0.035

NMI_kmeans

0.65 ± 0.033

0.61 ± 0.032

0.90 ± 0.028

0.63 ± 0.035

0.57 ± 0.031

0.55 ± 0.035

0.59 ± 0.039

Conflicting clustering

PCCintraclass

0.095 ± 0.0052

0.095 ± 0.0051

0.095 ± 0.0061

0.032 ± 0.0063

0.62 ± 0.023

0.53 ± 0.033

0.59 ± 0.035

PCCinterclass

−0.017 ± 0.0047

−0.020 ± 0.0049

−0.019 ± 0.0062

−0.0099 ± 0.0067

−0.20 ± 0.019

−0.18 ± 0.021

−0.19 ± 0.022

PCCintraclass-PCCinterclass

0.11 ± 0.011

0.12 ± 0.012

0.11 ± 0.013

0.042 ± 0.015

0.82 ± 0.037

0.71 ± 0.045

0.78 ± 0.051

Simintraclass

0.038 ± 0.0061

0.038 ± 0.0062

0.038 ± 0.0061

0.99 ± 0.00005

0.31 ± 0.024

0.27 ± 0.025

0.30 ± 0.029

Siminterclass

0 ± 0.0

0 ± 0.0

0 ± 0.0

0.99 ± 0.00007

0.11 ± 0.021

0.10 ± 0.020

0.12 ± 0.023

Simintraclass-Siminterclass

0.038 ± 0.0061

0.038 ± 0.0062

0.038 ± 0.0061

0.00019 ± 0.00010

0.20 ± 0.037

0.17 ± 0.039

0.18 ± 0.042

ACC_rfLOO

0.42 ± 0.020

0.51 ± 0.023

0.63 ± 0.031

0.93 ± 0.063

0.96 ± 0.034

0.94 ± 0.031

0.95 ± 0.036

NMI_kmeans

0.46 ± 0.033

0.49371 ± 0.034

0.84626 ± 0.045

0.11654 ± 0.081

0.92 ± 0.052

0.91 ± 0.053

0.92 ± 0.055

  1. The best performer was highlighted with the darkest color
  2. PCCintraclass: average Pearson correlation coefficients of patients within the same classes; PCCinterclass: average Pearson correlation coefficients of patients from different classes; Simintraclass: average similarity of patients within the same classes measured by the Gausian kernel;Siminterclass:average similarity of patients from different classes measured by the Gausian kernel;ACC_rfLOO: accuracy of leave-one-out cross-validation by random forest; NMI_kmeans: normalized mutual information between the true patient relationships and the clustering results by k-means