Getting Started with Sequencing Analysis

It has been a few weeks and I thought that I would give some updates on my progress so far. I’m currently replicating methods from the paper Sex Speeds adaptation by altering the dynamics of molecular evolution (1). This paper provides a useful computational workflow for identifying mutations from sequence data. This past month I have come across a huge learning curve, using software that I have never come across before, specifically GATK (Gene Analysis Toolkit). My first research task is sequencing analysis, and given that I have very minimal experience using sequencing software, it has been quite a challenge. Nonetheless, I have enjoyed learning a lot from this experience. From deciphering and creating pipelines, troubleshooting errors and running 50+ hours commands (we have a huge dataset), I’m getting closer to having a working dataset that I will use for analysis.

At the moment, I’m filtering my dataset so that I have high quality snps (single nucleotide polymorphisms) for analysis. This final data set will be a list of candidate mutations, that will enable me to visualize mutation frequencies across the control, sexual and asexual populations of S. cerevisiae. With this data, I plan to identify which mutations are being selected for or against across each population. This should lead me closer to getting an idea of the genetic architecture behind yeast’s ability to form a biofilm (which is the phenotype that we have selected for in our S. cerevisiae populations). In the meantime, I have been reading up on relevant papers to keep gaining knowledge on the topic. Asides from working at the computer, I have also gotten a chance to do some fun activities with our lab, like making a trip to Busch Gardens and watching Ocean’s 8. For the next few weeks, I hope to get a good chunk of analysis done with my refined dataset. I have enjoyed my time doing research so far and am looking forward to where the rest of the summer and upcoming school year will take me!

(1) M.J. McDonald, D.P. Rice, M.M. Desai, Sex speeds adaptation by altering the dynamics of molecular evolution, Nature, 531 (2016), pp. 233-236 


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