Clustering analysis of large-scale phenotypic data in the model filamentous fungus Neurospora crassa

Carrillo, Alexander J.; Cabrera, Ilva E.; Spasojevic, Marko J.; Schacht, Patrick; Stajich, Jason E.; Borkovich, Katherine A.

doi:10.1186/s12864-020-07131-7

BMC Genomics

Table 1 Comparison of results using different iterations of Partitioning Around Medoids (PAM)

From: Clustering analysis of large-scale phenotypic data in the model filamentous fungus Neurospora crassa

Weight^c	Number of Clusters	Average % consensus^a									Average relative standard deviation (RST)^b
Weight^c	Number of Clusters	Conidia number	Conidia morphology	Protoperithecia number	Protoperithecia morphology	Perithecia number	Perithecia morphology	Ascospore number	Ascospore morphology	Average % consensus overall	Basal hyphae growth rate	Aerial hyphae height	Average RST overall
0	18	91.72	94.20	93.74	94.23	95.27	93.34	96.35	98.32	95.06	26.76	34.12	13.20
0	19	92.16	94.50	94.05	94.51	95.45	93.66	96.48	98.39	95.29	25.33	32.54	12.76
0	20	92.50	94.78	94.35	94.79	95.68	93.92	96.66	98.47	95.52	24.62	30.43	12.36
0	21	93.02	95.19	94.61	95.04	95.88	94.21	96.81	97.03	95.54	28.30	31.30	13.09
1	31	95.92	96.57	93.46	94.99	95.70	95.39	97.32	98.76	96.03	19.80	24.13	11.02
1	32	95.22	96.66	94.40	95.98	95.84	95.53	97.40	98.80	96.37	20.18	24.55	10.44
1	33	95.67	97.05	94.57	96.11	95.97	95.67	97.47	97.95	96.40	22.57	25.24	10.92
2	32	96.23	94.89	94.02	95.04	94.22	95.51	98.76	98.82	95.90	17.52	26.50	10.88
2	33	96.35	95.05	94.20	95.19	94.31	95.64	98.79	98.86	96.01	16.91	25.83	10.67
2	34	95.45	95.24	94.99	96.82	94.47	95.77	98.82	98.89	96.43	17.55	26.30	10.22
2	35	95.15	94.62	95.00	96.91	93.95	94.98	98.03	98.09	95.94	18.98	25.30	11.19
3	29	96.20	96.09	93.25	94.20	92.63	95.26	95.53	97.62	94.94	13.77	27.67	10.82
3	30	96.37	96.22	93.47	94.39	92.88	95.34	95.67	97.70	95.10	13.43	26.61	10.60
3	31	97.45	97.64	91.71	94.52	94.39	94.05	95.14	96.63	94.87	15.60	27.08	10.98
3	32	97.45	97.29	92.26	94.54	93.62	93.38	95.46	96.91	94.78	15.46	27.69	11.41
3	33	96.92	96.53	92.41	94.65	93.28	92.81	95.29	96.69	94.52	17.58	26.11	12.14
4	32	90.89	94.99	93.99	95.11	94.39	94.23	94.57	97.20	94.93	14.23	18.81	11.42
4	33	90.50	94.98	93.99	94.80	94.13	93.80	94.40	97.37	94.78	14.21	19.08	11.96
4	34	90.78	94.78	94.10	94.83	94.76	94.13	94.97	97.46	95.01	14.10	20.18	11.75
4	35	90.82	94.93	94.27	94.98	94.91	94.23	95.11	97.53	95.14	13.78	19.68	11.57
5	36	85.84	95.66	94.14	95.40	95.38	93.87	94.33	97.42	95.17	14.09	13.44	11.26
5	37	85.28	95.45	94.18	95.41	95.51	94.04	94.48	97.49	95.22	13.99	12.45	11.22
5	38	85.18	95.55	94.88	95.63	94.53	94.15	94.03	97.55	95.19	13.90	12.05	11.20
5	39	84.56	95.62	95.24	96.70	94.67	94.30	94.18	97.61	95.48	13.93	12.46	11.00
5	40	84.36	95.37	96.40	96.26	94.37	94.01	94.33	97.67	95.49	13.80	12.71	10.96
6	39	89.07	95.73	94.33	94.58	93.57	93.70	93.89	97.39	94.03	14.11	11.64	11.03
6	40	89.64	95.83	94.22	94.71	93.73	93.86	94.04	97.45	94.19	13.94	11.86	10.98

^aAverage percent consensus - For each cluster the category that was most prevalent was determined and represented as a percent. Then each cluster’s most prevalent category was used to create a trait average
^bAverage relative standard deviation - For continuous variables, the standard deviation for each cluster was calculated and then divided by the cluster mean to determine the relative standard deviation
^cWeight - Each phenotype was assigned a specific weight relative to the other traits when creating the Gower’s distance matrix. The phenotypes are in the order as shown in Table 1
No weight = (1,1,1,1,1,1,1,1,1,1); Weight 1 = (1,1,1,1,1,1,1,1,2,2); Weight 2 = (1,0.5,1,0.5,1,0.5,1,0.5,2,2); Weight 3 = (2,2,1,1,1,1,1,1,6,2); Weight 4 = (0.5,0.5,1,1,1,1,1,1,6,5); Weight 5 = (1,1,1,1,1,1,1,1,6,4); Weight 6 = (1,1,1,1,1,1,1,1,6,6)

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