Acopula-Based Approach to Differential Gene Expression Analysis is the topic of research for faculty lecturer (Strathmore Institute of Mathematical Sciences – SIMS) Linda Chaba, who is set to graduate with her PhD this June.
Linda’s research worked at developing a copula-based algorithm for variable selection in high dimensional data. The algorithm was applied to microarray data to identify genes that were associated with quantitative traits. The identification of such types of genes may lead to a more accurate diagnostics and treatment at individual patient level.
What led you towards this particular research?
I knew I wanted to do biostatistics but I did not have this topic in mind when I started my PhD topic search. My supervisor whom I met for the first time at one of our international mathematics conferences, here at Strathmore University, shared with me a number of ideas I could work on. I was drawn to this topic even though I was not very familiar with what gene expression analysis and copula were all about. It is quite an interesting area of research and I’ll continue working on it in my coming days as a researcher.
What were your findings?
Our proposed copula-based approach had a good power to select differentially expressed genes (DEGs). The approach also showed good results in controlling type I error rates. When applied to the real datasets, the gene list generated by our proposed approach was a good predictor of a quantitative outcome. The method is therefore recommended for finding DEGs among other existing method.
Have you shared your findings with the Medical field?
Some of the papers generated from my work are already out in the public domain. Researchers from the biomemedical fields would find some of the results very useful. I’m willing to share the finer details with whoever maybe interested.
Did you face challenges while conducting this research?
I had a challenge getting data locally so I had to use data collected from the US. Balancing family, studies, and work was a big challenge but with the support I received from my family, my supervisors, and colleagues, I pulled through.
What gave you strength to push through?
The urge to become a better version of myself and to become a motivation to our future generations especially ladies interested in the STEM.
Also, having always been interested in being part of healthcare industry and impacting the health and well-being of others, I developed passion for science with a focus on Biostatistics. This passion inspired me to continue working to see my dream come true.
What do you feel about Women and Mathematics?
I believe women have analytical skills needed for mathematics. They are excellent in visualization, analysis, and interpretation. Most women shy away from mathematics due to the negative attitudes they developed towards math in their early days in school. Providing early interest and scholarships in STEM programs is paramount in encouraging more women in these fields perceived as masculine. Good news is that there has been an increase in the number of women perusing mathematics as a subject over the years.
How did your family react towards your love for numbers?
By now they are used to the idea. I believe to some extent, the love of numbers runs in our blood even though most of my family members have not done mathematics as a core subject. I loved mathematics since I was young. I started attending tuition for math because my class teacher noticed I was keen on it. I did not see the need, but I think my teacher used this method to motivate me further towards the subject.
Who can benefit from your research?
My work is beneficial to any research that involves variable selection in high-dimensional data (datasets with large number of features). Researchers interested in finding genes signatures that are associated with a disease outcome, for example, cancer or no cancer will find my research work quite useful.
How would you describe yourself?
I am a mother, a wife, a sister, and daughter to someone.
Professionally I am a lecturer, and a statistician. Or simply a lady who enjoys working with numbers.
What is your education background?
I attended Moi Girls High School-Eldoret where I finished in 2002. I then joined University of Nairobi in 2004 where I undertook a Bachelor of Science in statistics, graduating in 2008. In 2009 I went back to the same university to study a Master of Science in Biometry. I graduated in 2011.
While studying my Masters, I interned for a joint project with KEMRI and the University of Washington, after which I joined Strathmore University as a teaching assistant. I became an assistant lecturer after graduation.
My PhD journey began immediately after graduation, where I explored different topics of research. I defended my PhD proposal in November 2013 but officially registered as a PhD student in March 2014 at Strathmore University. I was supervised by Prof. Bernard Omollo from the University of South Carolina-Upstate, and Prof. John Odhiambo, the Vice Chancellor, Strathmore University.
What motivated you to keep going?
I was motivated by my family’s overwhelming support throughout the study period. My son got used to seeing mommy study, and learnt to cease the moment by pulling his desk next to mine whenever I was studying. I cannot thank my husband enough for his patience. Encouragements from my parents and their wishes to see me succeed were motivations enough. I am sure they are very proud of me. If you have father figures and mentors as your supervisors, what would stop you from moving on? I really appreciate their support.
When you’re not teaching and researching, what do you enjoy doing?
I love listening to music while cleaning whenever I have free time. Nothing beats spending time with family too.
From her PhD research, Linda has already published a paper; Evaluation of Methods for Gene Selection in Melanoma Cell Lines which can be accessed here.
She also published two papers before she began her PhD; Water Filter Provision and Home-Based Filter Reinforcement Reduce Diarrhea in Kenyan HIV-Infected Adults and Their Household Members access here; and Sexually transmitted infections among HIV-infected adults in HIV care programs in Kenya: A national sample of HIV clinics access here.
Congratulations to Linda Chaba on her great achievement.