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Table 1 ARIs of four feature selection methods combined with four clustering methods across 12 datasets

From: mCOPA: analysis of heterogeneous features in cancer expression data

Feature selection + clustering method Datasets* (Details presented in Additional file1– Public datasets)
Pr C Mn R1 R2 NPh Lm R3 B T Br L
COPA+CH 0.12 0.04 0.69 0.20 0.64 0.15 0.23 0.38 0.06 0.05 0.16 0.45
COPA+KM 0.30 0.16 0.53 0.62 0.33 0.31 0.25 0.54 0.09 0.23 0.12 0.41
COPA+PAM 0.13 0.18 0.60 0.90 0.81 0.36 0.26 0.57 −0.02 0.31 0.12 0.35
COPA+SIL 0.04 0.08 0.69 0.20 0.30 0.15 0.33 0.43 0.06 0.05 0.07 0.55
DE+CH 0.17 0.15 0.21 0.24 0.53 0.36 0.38 0.28 0.21 0.52 0.12 0.44
DE+KM 0.29 0.15 0.51 0.75 0.59 0.34 0.38 0.65 0.27 0.63 0.12 0.54
DE+PAM 0.35 0.13 0.24 0.79 0.76 0.34 0.26 0.56 0.11 0.46 0.16 0.43
DE+SIL 0.17 0.15 0.33 0.24 0.53 0.14 0.38 0.28 0.21 0.52 0.12 0.44
mCOPA+CH 0.29 0.15 0.60 0.55 0.40 0.35 0.38 0.39 0.06 0.52 0.11 0.30
mCOPA+KM 0.46 0.01 0.79 0.68 0.48 0.36 0.45 0.85 0.00 0.63 0.08 0.62
mCOPA+PAM 0.47 0.10 0.55 0.82 0.54 0.45 0.44 0.49 0.03 0.50 0.20 0.44
mCOPA+SIL 0.29 0.14 0.60 0.61 0.40 0.35 0.38 0.39 0.06 0.52 0.11 0.30
VAR+CH 0.14 0.08 0.69 0.32 0.34 0.28 0.38 0.57 0.02 0.26 0.13 0.45
VAR+KM 0.16 0.16 0.47 0.81 0.47 0.23 0.34 0.64 0.09 0.15 0.17 0.41
VAR+PAM 0.17 0.16 0.88 0.81 0.43 0.02 0.26 0.61 0.10 0.06 0.15 0.33
VAR+SIL 0.14 0.08 0.69 0.89 0.34 0.28 0.38 0.57 0.02 0.12 0.13 0.59
  1. Note: the ARI scores in italicized bold indicate the best performing method for each dataset. Datasets in bold indicate those in which mCOPA provided the most informative feature selection for the clustering of clinical subtypes.
  2. *Datasets: Pr (Prostate: GSE6099); C (Cervical: GSE7410); Mn (Melanoma: GSE7553); R1 (Renal: GSE11024); R2 (Renal: GSE11151); NPh (Nasopharangeal: GSE12452); Lm (Lymphoma: GSE12453); R3 (Renal: GSE15641); B (Brain: GSE15824); T (Thyroid: GSE29265); Br (Breast: GSE29431); L (Lung: GSE32036).