Case Study: The University of Chicago

The research goals of Carole Ober’s laboratory at the University of Chicago are to identify genetic variants that influence gene expression and epigenetic patterns in tissues relevant to complex phenotypes, especially related to asthma and fertility. The lab uses both freshly isolated cells, as well as tissue and cell culture models of gene-environment interactions to explore context-specific transcriptomic and epigenomic responses. The group of 13 people includes graduate students, postdoctoral students, a computer programmer (and database manager), technicians and research assistants, and a genetic counselor. The group is nearly evenly split between wet (experimental) work and computational/bioinformatic work. The Ober lab has maintained a multi-seat license for iPathwayGuide for over 3 years.

Britney Helling and Andréanne Morin are postdoctoral scholars in the Ober lab and are two of the users of iPathwayGuide from AdvaitaBio.

Britney received her PhD in human medical genetics and genomics from the University of Colorado, where she worked in a pulmonary-focused lab. Her research focused on a rare lung disease called idiopathic pulmonary fibrosis. For her thesis research, she did a lot of hands-on experimentation. As a post-doc in the Ober laboratory, her research expanded to include cell culture modeling, which produces the data that she analyzes with iPathwayGuide. Britney feels that she is now into the “heavy omics” analysis.

Andréanne Morin received a PhD, in human genetics, from McGill University. Her thesis research was computational, examining the role of rare variants in complex traits and how they impact gene expression. She also performed genetic association studies with asthma and asthma-related traits. At McGill, she focused on studies aimed to identify genetic variants that impact these traits, but since joining the Ober lab at University of Chicago she now also studying the role of environmental exposures and gene-environment interactions in asthma and related traits.

Interestingly, a graduate student recommended iPathwayGuide to the lab, based on their research in another lab before starting graduate school. When the license on a different pathway program that the lab used was up for renewal, they decided to consider other options. It was then that the team looked closely at iPathwayGuide and both its range of applications as well as the price. Based on both considerations, they determined that iPathwayGuide was a better fit for their overall needs. Andréanne says: “There were many different elements that really made the lab choose iPathwayGuide instead of Ingenuity Pathway Analysis. I think Advaita also offered better customer service.”

Britney says: “We handle a lot of big data. The results from our experiment aren’t just a single gene or a single pathway change, but more widespread changes that happen across the entire genome. When you have hundreds or thousands of different, in my case, RNASeq data, iPathwayGuide allows us to make sense of the data without having to go through each individual gene and determine what its function is, and how the genes are related.”

When asked what they like better about iPathwayGuide compared to other platforms, Andréanne goes on to say: “For my last project, I liked that I was to be able to put the direction of effect for each gene into software. My study integrated early life microbiome and DNA methylation. I generated a list of genes for which the expression correlated with a methylation signature and then used iPathwayGuide to generate the pathways that included these correlated genes. Other platforms provided very broad pathways, and kind of made sense, but they were not as specific to the outcomes of our study. iPathwayGuide revealed relatively specific pathways that made sense with the results of the study. Adding their effect size of the correlation, I was able to find other pathways that were not revealed by other software platforms.”

She adds: “I didn’t look just at gene expression directly in a pathway analysis, but rather used as input genes whose expression was correlated with a DNA methylation signature of early life exposures. iPathwayGuide identified “bacterial invasion of epithelial cell”, which captured a mechanistic pathway that matched our data on microbiome exposure in early life and DNA methylation patterns in epithelial cells. In contrast, the pathways identified with other software were immune-related but not specific to epithelial cells or microbiota. The results of the iPathwayGuide analyses was really a “wow”! it made sense with my results and strengthened the conclusions of my paper.”

Britney adds: “We are also finding that the user interface for iPathwayGuide is very user-friendly and there are places to report questions or suggest things that could be modified.” She adds: “It makes the process really easy. There’s a lot that you can go through when you submit even a simple list of genes. Some of those can be outside of our wheelhouse, such as how drugs interact with our pathways, but they have video clips that teach us about any gaps that we may have. The Advaita staff are very responsive to comments, questions and concerns. I think that made it a little bit easier to understand in more details what’s going on.”

Britney says that her favorite part of iPathwayGuide is the multitude of ways you can view the data. “So many different scopes” she says. Andréanne agrees and says that it helps her to make more sense of the results.

Britney states that there are a number of benefits of iPathwayGuide compared to other pathway programs. She says: “With the previous program we used, only one person could use the platform at a time, which was very inconvenient. With iPathwayGuide, you can evaluate your data for hours without holding up others from viewing their results. This has been a very important improvement for us.”

Andréanne says that the transition process from Ingenuity Pathway Analysis to iPathwayGuide was simple and straightforward. There were no issues at all: “It was easy to use right from the beginning.”

Britney says: “We talk about the customer service a lot, but the fact is that a lot of vendors put out these products and they are what they are. AdvaitaBio is not just responsive to our questions, but immediately responsive. Every time I’ve emailed them, they responded in less than 24 hours. They have been both willing to make changes to the platform and eager to hear suggestions, something that we have found to be very helpful and very unusual.” Andy adds: “The platform has improved since we got our first license, with the addition of more types of analyses and constantly evolving into a better and better platform.”

Both Andréanne and Britney agree that they would recommend iPathwayGuide and AdvaitaBio to others. They say that “between the quality of the software, the licensing flexibility and the better service, that this is the best option available for our research. “