Background: The development of next generation sequencing (NGS) methods led to a rapid rise in the generation of large genomic datasets, but the development of user-friendly tools to analyze and visualize these datasets has not developed at the same pace. This presents a two-fold challenge to biologists; the expertise to select an appropriate data analysis pipeline, and the need for bioinformatics or programming skills to apply this pipeline. The development of graphical user interface (GUI) applications hosted on web-based servers such as Shiny can make complex workflows accessible across operating systems and internet browsers to those without programming knowledge.Results: We have developed GENAVi (Gene Expression Normalization Analysis and Visualization) to provide a user-friendly interface for normalization and differential expression analysis (DEA) of human or mouse feature count level RNA-Seq data. GENAVi is a GUI based tool that combines Bioconductor packages in a format for scientists without bioinformatics expertise. We provide a panel of 20 cell lines commonly used for the study of breast and ovarian cancer within GENAVi as a foundation for users to bring their own data to the application. Users can visualize expression across samples, cluster samples based on gene expression or correlation, calculate and plot the results of principal components analysis, perform DEA and gene set enrichment and produce plots for each of these analyses. To allow scalability for large datasets we have provided local install via three methods. We improve on available tools by offering a range of normalization methods and a simple to use interface that provides clear and complete session reporting and for reproducible analysis.Conclusion: The development of tools using a GUI makes them practical and accessible to scientists without bioinformatics expertise, or access to a data analyst with relevant skills. While several GUI based tools are currently available for RNA-Seq analysis we improve on these existing tools. This user-friendly application provides a convenient platform for the normalization, analysis and visualization of gene expression data for scientists without bioinformatics expertise.

Objective: Genome-wide association studies have identified multiple Crohn's disease (CD) susceptibility loci, including association with non-coding intergenic single-nucleotide polymorphisms (SNPs) at 10q21. Design: To fine-map the 10q21 locus, the authors genotyped 86 SNPs in 1632 CD cases and 961 controls and performed single-marker and conditional analyses using logistic regression. Results: Association with CD risk spanning 11 SNPs (p<0.001) was observed. The most significant association observed was at the non-synonymous SNP, rs7076156 (Ala62Thr), in ZNF365 . The alanine allele was over-represented in CD (p=5.23×10 ⁻⁷ ; OR=1.39 (95% CI 1.22 to 1.58)); allele frequency of 76% in CD and 69.7% in controls). Conditional analysis on rs7076156 nullified all other significant associations, suggesting that this is the causative variant at this locus. Four isoforms of ZNF365 have previously been identified, and rs7076156 is located in an exon unique to ZNF365 isoform D. The authors demonstrated, using reverse transcription-PCR, expression of ZNF365D in intestinal resections from both CD subjects and controls. Markedly reduced mean expression levels of ZNF365D were identified in Epstein–Barr virus-transformed lymphoblastoid cell lines from CD subjects homozygous for the risk allele (Ala). A whole-genome microarray expression study further suggested that the Ala62Thr change in ZNF365 isoform D is related to differential expression of the genes ARL4A , MKKS , RRAGD , SUMF2 , TDR1 and ZNF148 in CD. Conclusions: Collectively, these data support the hypothesis that the non-synonymous Ala62Thr SNP, rs7076156, underlies the association between 10q21 and CD risk and suggest that this SNP acts by altering expression of genes under the control of ZNF365 isoform D.

Context: Increased androgen production is a primary feature of polycystic ovary syndrome (PCOS) and appears to be an inherited trait. The gene for the steroidogenic enzyme type 5 17β hydroxysteroid dehydrogenase (HSD17B5) was implicated as a candidate for the hyperandrogenemia of PCOS by a previous study that demonstrated an association of a single nucleotide polymorphism (SNP) in the promoter of this gene with PCOS. Objective: The objective of the study was to replicate the previous report of association between the HSD17B5 gene and PCOS risk by genotyping the promoter SNP (as well as other SNPs in the region to provide improved coverage of the gene) in a large, well-characterized cohort suitable for replication study. Design: Women with and without PCOS were genotyped for five SNPs in HSD17B5. SNPs and haplotypes were determined and tested for association with PCOS risk and phenotypic markers of PCOS. Setting: Subjects were recruited from the reproductive endocrinology clinic at the University of Alabama at Birmingham; controls were recruited from the surrounding community. Genotyping took place at Cedars-Sinai Medical Center in Los Angeles. Participants: Participants included 287 white women with PCOS and 187 white controls. Main Measurements:HSD17B5 genotype, PCOS risk, and testosterone levels were measured. Results: No SNP or haplotype was significantly associated with PCOS risk, testosterone, or any of the traits tested. Conclusions: These data suggest that polymorphisms in the HSD17B5 gene are not associated with PCOS risk or elevated testosterone as previously reported.