Identification of novel biomarkers in Hunner’s interstitial cystitis using the CIBERSORT, an algorithm based on machine learning

Table 1 33 KEGG pathways of HIC related autoimmune and infectious diseases

No.	Description	Set size	Enrichment score	p value adjusted
1	Graft-versus-host disease	35	0.82	0.01
2	Intestinal immune network for IgA production	43	0.80	0.01
3	Rheumatoid arthritis	84	0.77	0.01
4	Malaria	46	0.77	0.01
5	Systemic lupus erythematosus	46	0.77	0.01
6	Asthma	26	0.76	0.01
7	Autoimmune thyroid disease	46	0.75	0.01
8	Type I diabetes mellitus	39	0.74	0.01
9	Leishmaniasis	71	0.73	0.01
10	Inflammatory bowel disease	61	0.70	0.01
11	Legionellosis	53	0.68	0.01
12	Pertussis	69	0.68	0.01
13	African trypanosomiasis	34	0.65	0.01
14	Tuberculosis	169	0.61	0.01
15	Viral myocarditis	54	0.61	0.01
16	Staphylococcus aureus infection	75	0.60	0.01
17	Measles	130	0.59	0.01
18	Epstein-Barr virus infection	191	0.59	0.01
19	Kaposi sarcoma-associated herpesvirus infection	183	0.58	0.01
20	Prion diseases	34	0.58	0.04
21	Toxoplasmosis	104	0.58	0.01
22	Influenza A	157	0.56	0.01
23	Human T-cell leukemia virus 1 infection	213	0.56	0.01
24	Hepatitis B	158	0.54	0.01
25	Human cytomegalovirus infection	214	0.51	0.01
26	Acute myeloid leukemia	66	0.50	0.02
27	Yersinia infection	117	0.46	0.01
28	Viral carcinogenesis	162	0.45	0.01
29	Human immunodeficiency virus 1 infection	196	0.44	0.01
30	Hepatitis C	149	0.39	0.05
31	Shigellosis	207	0.37	0.03
32	Salmonella infection	211	0.37	0.03
33	Human papillomavirus infection	317	0.33	0.04

ISSN: 1471-2490