![](https://static.wixstatic.com/media/09bc8e_928497613c2449a7861b2363b92c2fdc~mv2.jpg/v1/fill/w_288,h_166,al_c,q_80,usm_0.66_1.00_0.01,blur_2,enc_auto/09bc8e_928497613c2449a7861b2363b92c2fdc~mv2.jpg)
Jennifer Fouquier, PhD
Providing analytic services for EXPLANA
Welcome
Hello! I created this website to help others analyze their data using EXPLANA, a workflow that implements machine-learning methods to perform feature selection. I developed EXPLANA while pursuing my PhD in the Lozupone Lab at The University of Colorado Anschutz Medical Campus. Using EXPLANA requires a solid computational background, so I created this website for those who might not have the right team (or time!) to do it on their own. I'm additionally interested in custom projects so feel free to contact me or schedule time to talk. Thank you for visiting!
![](https://static.wixstatic.com/media/11062b_e12e778250c54ec0aa0d967b228e9cc3f000.jpg/v1/fill/w_117,h_66,al_c,q_80,usm_0.66_1.00_0.01,blur_2,enc_auto/11062b_e12e778250c54ec0aa0d967b228e9cc3f000.jpg)
ABOUT
Challenge
Researchers often want to identify the most important features that relate to outcome values in scientific studies. However, there are many analytic challenges, including:
​
Lots of data and literature to understand, non-linear relationships, non-normal data distributions, how to handle both categorical and numerical variables, etc.
​
It is cumbersome to keep track of the analytics used for obtaining a set of interesting features.
![EXPLANA-black-reverse.png](https://static.wixstatic.com/media/09bc8e_21fc4f701227459e8df91ea42d22c563~mv2.png/v1/fill/w_232,h_68,al_c,q_85,usm_0.66_1.00_0.01,enc_auto/EXPLANA-black-reverse.png)
Solution
I developed EXPLANA (EXPLoratory ANAlysis) to generate an interactive report containing figures and written descriptions of the methods summarizing the steps taken for feature selection.
​
EXPLANA can identify unique features dependent on different contexts of change (for observational and interventional longitudinal study designs), including novel order-dependent categorical features.
EXPLANA was designed for longitudinal microbiome studies, but works for cross-sectional studies too, and is broadly useful for various applications as a general feature selection tool.
Services
Tell me about your research! This website provides a place for you to book virtual appointments with me to plan exploratory analyses. I will send you reports within 10 business days.
​
I am also interested in custom projects related or unrelated to EXPLANA.
​
Your data will always be kept confidential and secure.
​
If you are interested in licensing EXPLANA for commercial use please contact:
(reference invention ID: CU6153H)
EXPLANA report
![new-screenshot.png](https://static.wixstatic.com/media/09bc8e_e2633ee7a7814a918429f9e49ce67f2d~mv2.png/v1/fill/w_70,h_39,al_c,q_85,usm_0.66_1.00_0.01,blur_2,enc_auto/new-screenshot.png)
![](https://static.wixstatic.com/media/09bc8e_9864a46e1f81406796da4859e40b371e~mv2.jpg/v1/fill/w_62,h_94,al_c,q_80,usm_0.66_1.00_0.01,blur_2,enc_auto/09bc8e_9864a46e1f81406796da4859e40b371e~mv2.jpg)
Jennifer Fouquier
​
PhD, Computational Bioscience
The University of Colorado, Anschutz Medical Campus, Aurora, CO
​
MS, Bioinformatics and Medical Informatics
San Diego State University, San Diego, CA
​
BS, Microbiology
The University of California, San Diego, La Jolla, CA
​
Experience:
10 yrs wet lab | 12 yrs computational