Additional file 1: of Copy number alterations detected by whole-exome and whole-genome sequencing of esophageal adenocarcinoma

Supplementary tables. Table S1. Cancer genes in detected amplification regions. Table S2. Cancer genes in detected deletion regions. Table S3. Comparison of results of Frankel to our results. Table S4. Comparison of results of Paulson to our results. Table S5. Comparison of results of Beroukhim to our results. Table S6. Comparison of results of Zack to our results. Table S7. Ploidy information of the 15 EA samples. (XLSX 57.4 kb

Assessment of the relationship between pre-chip and post-chip quality measures for Affymetrix GeneChip expression data.

Background Gene expression microarray experiments are expensive to conduct and guidelines for acceptable quality control at intermediate steps before and after the samples are hybridised to chips are vague. We conducted an experiment hybridising RNA from human brain to 117 U133A Affymetrix GeneChips and used these data to explore the relationship between 4 pre-chip variables and 22 post-chip outcomes and quality control measures. Results We found that the pre-chip variables were significantly correlated with each other but that this correlation was strongest between measures of RNA quality and cRNA yield. Post-mortem interval was negatively correlated with these variables. Four principal components, reflecting array outliers, array adjustment, hybridisation noise and RNA integrity, explain about 75% of the total post-chip measure variability. Two significant canonical correlations existed between the pre-chip and post-chip variables, derived from MAS 5.0, dChip and the Bioconductor packages affy and affyPLM. The strongest (CANCOR 0.838, p < 0.0001) correlated RNA integrity and yield with post chip quality control (QC) measures indexing 3'/5' RNA ratios, bias or scaling of the chip and scaling of the variability of the signal across the chip. Post-mortem interval was relatively unimportant. We also found that the RNA integrity number (RIN) could be moderately well predicted by post-chip measures B_ACTIN35, GAPDH35 and SF. Conclusion We have found that the post-chip variables having the strongest association with quantities measurable before hybridisation are those reflecting RNA integrity. Other aspects of quality, such as noise measures (reflecting the execution of the assay) or measures reflecting data quality (outlier status and array adjustment variables) are not well predicted by the variables we were able to determine ahead of time. There could be other variables measurable pre-hybridisation which may be better associated with expression data quality measures. Uncovering such connections could create savings on costly microarray experiments by eliminating poor samples before hybridisation

Characteristics of Cases and Controls in the Multiethnic Cohort Study (MEC) and the Women's Health Initiative Study (WHI).

1<p>Age at diagnosis for cases and age at blood draw for controls in the MEC; age at baseline for cases and controls in the WHI.</p>2<p>Japanese in the MEC, approximately 25% Chinese, 50% Japanese, and 25% other groups in the WHI.</p

Association between <i>HNF1B</i> variants and endometrial cancer.

1<p>Odds ratio per allele obtained from logistic regression adjusting for age (continuous), 4 ancestry principal components, BMI (<25, 25-<30, ≥30 kg/m²).</p>2<p>P interaction with race/ethnicity in the MEC ≥0.63; P interaction with race/ethnicity in the WHI ≥0.21;</p>3<p>Combined ORs were calculated using a fixed effects model.</p

Association between <i>HNF1B</i> variants and Type I and Type II endometrial cancer.

1<p>Odds ratio per allele obtained using polytomous logistic regression adjusting for age (continuous), 4 ancestry principal components, and BMI (<25, 25-<30, ≥30 kg/m²).</p>2<p>Combined ORs were calculated using a fixed effects model.</p

Tissue-specific gene expression of <i>RBFOX1</i> from GTEx database (http://www.gtexportal.org/home/gene/RBFOX1).

<p>Tissue-specific gene expression of <i>RBFOX1</i> from GTEx database (<a href="http://www.gtexportal.org/home/gene/RBFOX1" target="_blank">http://www.gtexportal.org/home/gene/RBFOX1</a>).</p

Association between <i>HNF1B</i> variants and endometrial cancer by diabetes status.

1<p>Odds ratio per allele obtained from logistic regression adjusting for age (continuous), 4 ancestry principal components and BMI.</p>2<p>Combined ORs were calculated using a fixed effects model.</p><p>Test for interaction was assessed using log-likelihood test statistics comparing models with and without the interaction term.</p><p>P interaction for rs4430796 was 0.028 (WHI) and 0.93 (MEC); P interaction for rs7501939 was 0.054 (WHI) and 0.58 (MEC).</p

The CFS family carrying the protective rare variant rs149974858.

<p>A) The variant rs149974858 segregates with BP in a 17-member CFS family. Squares represent males and circles represent females. Half-filled subjects represent the carriers of the rare variant rs149974858. Grey subjects represent no information. Age of each subject is presented in parenthesis. B) The distribution of corresponding residuals of SBP, DBP, PP and BMI are presented.</p

Linkage region on chromosome 16 of white participants in CFS.

<p>Linkage peak on chromosome 16 for SBP. The linkage curves are plotted with (red curve) and without (blue curve) adjusting for the risk score defined by the 13 coding variants as a covariate. The positions of the 13 coding variants are listed under the linkage peak and above the genes.</p

Results of gene-based analysis in discovery data and replication cohorts.

<p>Results of gene-based analysis in discovery data and replication cohorts.</p