Additional file 1 of Vaccination and the risk of systemic lupus erythematosus: a meta-analysis of observational studies

Supplementary Material 1: Supplementary Fig. S1. Sensitivity analysis of the risk of SLE caused by any vaccin

Additional file 1: Table S1. of Whole blood gene expression and white matter Hyperintensities

Association of top genes with WMH after excluding samples with stroke, dementia or vascular diseases. Table S2. Association of top genes with WMH after additionally adjusted for the RNA integrity number (RIN). Table S3. Separated analysis for participants from the Offspring cohort and the Third Generation cohort. Table S4. Association of top genes within cognitive performance. Figure S1. Correlation between the statistics of WMH associations derived from the imputed cell counts or the measured cell counts using those samples who have measured cell counts. X-axis represents the statistics derived from measured cell counts, while y-axis represents the statistics derived from the imputed cell counts. Strong correlation was observed (R2 = 0.984), suggesting only marginal effect of imputed cell counts. (PDF 187 kb

Additional file 1: of Quantitative metagenomics reveals unique gut microbiome biomarkers in ankylosing spondylitis

Table S1. Phenotype information of AS patient individuals and health controls in discovery stage (156 samples) and validation stage (55 samples). Table S2. Data production and quality control of 156 samples in discovery stage and 55 samples in validation stage. Table S3. The 8743 reference genomes from NCBI and HMP (downloaded on 15 Dec 2013). Table S4. The differentially abundant genus in AS patients (n = 73) and healthy controls (n = 83). Table S5. Assembly result of 156 samples in discovery stage. Table S6. The improvement with the repeatedly assembly. Table S7. Gene prediction of 156 samples in discovery stage. Table S8. Genes with abundance which belong to proteasome modules. All the differentially abundant genes identified in this study only belong to bacterial proteasome. Table S9. The taxonomic annotation of MGSs. Table S10. The phenotypic correlation analysis (p value) of 12 MGSs according to different clinical groups. Table S11. Comparison of the MGS in different diseases. Table S12. The taxonomic annotation of CAGs (Gene number ≥ 100). Table S13. The details of the best markers selected for five monitoring and classification models based on five kinds of bio-markers. Table S14. The 210 differentially abundant sequenced reference genome markers used for classification training. (XLSX 870 kb

Additional file 2: of Quantitative metagenomics reveals unique gut microbiome biomarkers in ankylosing spondylitis

Figure S1a. Venn diagram of three existing human gut gene catalogs. Figure S1b. Diversity of genera and species between AS patients and healthy controls. Figure S2. The Bacteroidetes/Firmicutes ratio in the AS patient group and in the healthy control group. Figure S3. Phylogenetic abundance under phylum, genus, and species levels between AS patients and healthy controls. Figure S4. Loss of richness of the gut microbiome in AS. Figure S5. The distribution of p values. Figure S6. The distribution of KEGG functional categories (statistics in Level 2) for all genes and differentially abundant genes. Figure S7. The distribution of detail pathways in four KEGG functional categories which were quite different between AS-enriched genes and control-enriched genes in Figure S6. Figure S8. The distribution of eggNOG functional categories for AS related markers. Figure S9. The distribution of KEGG module categories for AS related markers shown by number and percentage. Figure S10. Heatmap of the abundance of a random metagenomic species in both sequencing data and downloaded data. Figure S11. Taxonomic annotation of genes in CAGs by NT database. Figure S12. The NMDS (non-metric multidimensional scaling) analysis based on phylogenetic abundance profiling of all the 156 samples in the discovery cohort. (DOCX 4671 kb

Additional file 3: of Exome-chip meta-analysis identifies novel loci associated with cardiac conduction, including ADAMTS6

Video S1. (Quicktime) Video to illustrate the DORV phenotype finding in an Adamts6 mutant heart. (MOV 1983 kb

Additional file 2: of Exome-chip meta-analysis identifies novel loci associated with cardiac conduction, including ADAMTS6

Figure S1. Manhattan plot for European and African-American ancestry single variant analysis. Figure S2. Quantile-quantile plot for European and African-American ancestry single variant analysis. Figure S3. Manhattan plot for EA single variant analysis. Figure S4. QQ plot for EA single variant analysis. Figure S5. Manhattan plot for AA single variant analysis. Figure S6. Quantile-quantile plot for AA single variant analysis. Figure S7. Miami plot European and African-American ancestry sex-stratified single variant analysis. Figure S8. Quantile-quantile plots for European and African-American ancestry sex-stratified single variant analyses. Figure S9. Normal morphology of adult Adamts6 heterozygous hearts. (DOCX 4290 kb