| 1. |
- Deng, Min, et al.
(författare)
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Genome-wide association analyses in Han Chinese identify two new susceptibility loci for amyotrophic lateral sclerosis
- 2013
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Ingår i: Nature Genetics. - : Nature Publishing Group. - 1061-4036 .- 1546-1718. ; 45:6, s. 697-
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Tidskriftsartikel (refereegranskat)abstract
- To identify susceptibility genes for amyotrophic lateral sclerosis (ALS), we conducted a genome-wide association study (GWAS) in 506 individuals with sporadic ALS and 1,859 controls of Han Chinese ancestry. Ninety top SNPs suggested by the current GWAS and 6 SNPs identified by previous GWAS were analyzed in an independent cohort of 706 individuals with ALS and 1,777 controls of Han Chinese ancestry. We discovered two new susceptibility loci for ALS at 1q32 (CAMK1G, rs6703183, P-combined = 2.92 x 10(-8), odds ratio (OR) = 1.31) and 22p11 (CABIN1 and SUSD2, rs8141797, P-combined = 2.35 x 10(-9), OR = 1.52). These two loci explain 12.48% of the overall variance in disease risk in the Han Chinese population. We found no association evidence for the previously reported loci in the Han Chinese population, suggesting genetic heterogeneity of disease susceptibility for ALS between ancestry groups. Our study identifies two new susceptibility loci and suggests new pathogenic mechanisms of ALS.
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| 2. |
- Zhao, Wenhao, et al.
(författare)
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Comparison and application of SOFM, fuzzy c-means and k-means clustering algorithms for natural soil environment regionalization in China
- 2023
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Ingår i: Environmental Research. - : Elsevier. - 0013-9351 .- 1096-0953. ; 216
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Tidskriftsartikel (refereegranskat)abstract
- Soil attributes and their environmental drivers exhibit different patterns in different geographical directions, along with distinct regional characteristics, which may have important effects on substance migration and transformation such as organic matter and soil elements or the environmental impacts of pollutants. Therefore, regional soil characteristics should be considered in the process of regionalization for environmental management. However, no comprehensive evaluation or systematic classification of the natural soil environment has been established for China. Here, we established an index system for natural soil environmental regionalization (NSER) by combining literature data obtained based on bibliometrics with the analytic hierarchy process (AHP). Based on the index system, we collected spatial distribution data for 14 indexes at the national scale. In addition, three clustering algorithms—self-organizing feature mapping (SOFM), fuzzy c-means (FCM) and k-means (KM)—were used to classify and define the natural soil environment. We imported four cluster validity indexes (CVI) to evaluate different models: Davies-Bouldin index (DB), Silhouette index (Sil) and Calinski-Harabasz index (CH) for FCM and KM, clustering quality index (CQI) for SOFM. Analysis and comparison of the results showed that when the number of clusters was 13, the FCM clustering algorithm achieved the optimal clustering results (DB = 1.16, Sil = 0.78, CH = 6.77 × 106), allowing the natural soil environment of China to be divided into 12 regions with distinct characteristics. Our study provides a set of comprehensive scientific research methods for regionalization research based on spatial data, it has important reference value for improving soil environmental management based on local conditions in China.
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