Results - MIA - CNCB-NGDC

Results For Task ID: 9cab48ab7b9c4dac833d19ce52831dc4

Clustering / Labeled Visualization

Top features:

Heatmap

Feature Gene Identification

Feature gene is defined as score>0. The Score is the feature importance index (-1,1) for classification or subtyping calculated by the random forest algorithm.

Rank	Feature Gene	Score
1	CD48	0.988028
2	NUDC	0.945298
3	PREP	0.896984
4	ZNF8	0.788328
5	MIOX	0.755394
6	GUCA1A	0.684091
7	STIL	0.65675
8	LIMK2	0.610448
9	CSGALNACT2	0.608094
10	PTK7	0.607124
11	PDHB	0.542081
12	OIT3	0.498698
13	TTC18	0.44092
14	CACNB2	0.432395
15	CAMK2G	0.414445
16	ZNF37A	0.408389
17	GPR111	0.399203
18	TACR2	0.38036
19	ZCCHC24	0.379044
20	TEX15	0.366941
21	ORAI3	0.354901
22	CASP4	0.354816
23	TMEM179B	0.350247
24	FUCA2	0.347965
25	HSF4	0.329035
26	BDKRB2	0.325158
27	NEBL	0.32076
28	MAPK1IP1L	0.313791
29	SLC6A19	0.312604
30	OAF	0.304509
31	BMP1	0.301919
32	SEC23A	0.292971
33	SHOX2	0.279698
34	RAB18	0.279225
35	PRSS1	0.269889
36	FAM107B	0.266554
37	NXT1	0.2586
38	SERPINB2	0.25645
39	PSMG2	0.254268
40	LTBP1	0.253511
41	CALU	0.249929
42	BCL7C	0.232767
43	CACNA2D1	0.230291
44	UBE2C	0.226592
45	MKX	0.223067
46	ZNHIT2	0.215278
47	HOXC6	0.203885
48	OSCAR	0.198196
49	FLOT2	0.196987
50	SPRR4	0.191842
51	ZC3H18	0.189741
52	SH3RF2	0.174025
53	KRT16	0.172293
54	SAMHD1	0.169295
55	ANKRD2	0.167077
56	PCGF5	0.156329
57	MRPL32	0.153739
58	IFNA8	0.152801
59	HDAC4	0.152784
60	AOAH	0.151977
61	ATAD1	0.149119
62	WBSCR16	0.147947
63	KHDRBS3	0.146733
64	HIPK1	0.143926
65	POLR2J2	0.1432
66	PI3	0.141864
67	OLAH	0.141049
68	COL5A2	0.137172
69	KLK1	0.136191
70	MT1X	0.136169
71	C1orf228	0.134885
72	SLCO2B1	0.134172
73	CADM1	0.133658
74	NAALAD2	0.132779
75	PPIA	0.130905
76	APOBEC3C	0.129229
77	ZNF398	0.125729
78	FAM49A	0.122637
79	BAZ1B	0.119736
80	TUBGCP6	0.119302
81	TLCD1	0.119034
82	TOMM22	0.114795
83	RNF138	0.108155
84	OPALIN	0.10803
85	GNAZ	0.1066
86	LBX1	0.103419
87	IKZF5	0.100589
88	HERPUD1	0.0974698
89	CNPY4	0.096888
90	CD36	0.0946224
91	NECAB3	0.0946066
92	MRPL37	0.0870411
93	C9	0.0819983
94	PUM1	0.0551607
95	ABCC3	0.0550801
96	SSU72	0.0545075
97	POLR2J	0.0486099
98	NPPB	0.0453884
99	DDX49	0.0439599
100	EPB41L1	0.0439061
101	RAB42	0.0356713
102	SPRED3	0.0348833
103	TMEM106A	0.0246111
104	RAC1	0.020582
105	EIF1	0.0190138
106	ABCB1	0.0173974

Run Log

start time: 2021-12-17 22:26:11


input parameters:

Input dataset 1: glioma_CNV.txt
Input dataset 2: glioma_methylation.txt
Sample label: label.txt
sample number: 569
feature number: 500
data type number: 2
randomForest algorithm........

parameters:

classification parameter: class(K) = 3
the feature number: 500

end time: 2021-12-17 22:27:31


results:

The result of feature importance is in the file: 
feature_importance.txt

The raw dataset(s) ordered by important features is in the file: 
glioma_CNV_orderByImportance.txt
glioma_methylation_orderByImportance.txt