21 research outputs found
Additional file 13: of Genetic structure, divergence and admixture of Han Chinese, Japanese and Korean populations
Figure S11. Models used in gene flow study. (A) Model of D test. X is an out group, we put CEU or YRI in X; W is the contributor while Y and Z are the receivers. By comparing the two allelic patterns BABA and ABBA, we can infer the relationship of scale of gene flow between W to Y and W to Z. (PDF 30 kb
態度接近性とネガティブ気分の確かさが意思決定に及ぼす影響
In recent years, many studies said that moods had effects on information processing. Sensui (2006) examined how attitude accessibility and the certainty of positive moods influenced attitudes and behaviors. He assumed that people controlled easy automatic processing and used systematic processing on positive moods of certainty. On the other hand, the moods of uncertainty influenced their assessments. People used automatic processing on the moods of uncertainty. There are the reasons why he assumed so. First, they had the motivation to make sense of them. Second, positive events were easy to be activated from memory. Third, positive moods would last longer in conditions as mentioned above. This study examined how attitude accessibility and certainty of negative moods influence attitudes and behaviors. As a result, the stronger accessibility was, the higher assessments for brands and buying behaviors were on negative moods of certainty. This was supposed that negative events were difficult to be activated from memory because those causes were certain, people used automatic processing based on accessibility. On the other hand, the stronger accessibility was, the lower assessments were on negative moods of uncertainty. This was supposed that negative moods were easy to be activated from memory because those causes were uncertain, people used systematic processing used in negative moods, but when accessibility was strong, brands and negative moods were related
Additional file 10: of Genetic structure, divergence and admixture of Han Chinese, Japanese and Korean populations
Figure S8. STRUCTURE Analysis of ten East Asian populations. Results from K = 2 to K = 6 are shown. Each vertical bar represents an individual and each color stands for a genetic component (generated by R 2.15.2). (PDF 152 kb
Additional file 2: of Genetic structure, divergence and admixture of Han Chinese, Japanese and Korean populations
Table S2. Global FST values between East Asian populations and world-wide groups. (DOCX 16 kb
Additional file 3: of Genetic structure, divergence and admixture of Han Chinese, Japanese and Korean populations
Table S1. Genotype data used in this research. (DOCX 21 kb
Additional file 5: of Genetic structure, divergence and admixture of Han Chinese, Japanese and Korean populations
Figure S3. Principle component analysis (PCA). (A~B) PCA results of East Asian groups with CEU and YRI. (C) PCA result of groups within East Asia populations, excluding JPRK individuals for a higher marker density. (D) PCA result of four East Asian populations, including Han Chinese, Japanese and Koreans samples. (PDF 2458 kb
Additional file 6: of Genetic structure, divergence and admixture of Han Chinese, Japanese and Korean populations
Figure S4. K-means Cluster of PCA results. The results of Figure S3D were used to conduct the K-means cluster. Individuals that cluster together according to the top 10 PCs would be painted by the same color. Results of K = 3 and K = 4 are shown (generated by R 2.15.2). (PDF 116 kb
Additional file 11: of Genetic structure, divergence and admixture of Han Chinese, Japanese and Korean populations
Figure S9. Cross-validation (CV) plot for the Admixture analysis. Result of K = 3 to K = 7 are shown. (PDF 158 kb
Additional file 12: of Genetic structure, divergence and admixture of Han Chinese, Japanese and Korean populations
Table S3. Part of F3 test results. (DOCX 18 kb
Additional file 9: of Genetic structure, divergence and admixture of Han Chinese, Japanese and Korean populations
Figure S7. STRUCTURE analysis of East Asian samples with worldwide populations. Results from K = 3 to K = 7 are shown. Each vertical bar represents an individual and each color stands for a genetic component (generated by R 2.15.2). (PDF 141 kb