whoami

I am post doctoral fellow in the Kaiser lab, where I also earned my PhD. I spent my graduate work building the foundations of my doctorial thesis and now I am finally in the 'seq' phase that I have always looked forward to. I am fortunate to work for a boss that has been patient with me while I inched my way from raw data to the glorious heatmap. Analyzing my own data has been a beast of an experience and was a large motivation in starting the Bioinformatics Support Group. Data analysis can be overwhelming to begin and frustrating to power through but I hope together we can build a supportive community to overcome our analysis obstacles and understand our own data a little better.

Current projects: RNA-seq analysis

Upcoming projects: ChIP-seq and ATAC-seq analyses

Interested in learning:

• All of the plots! Always excited to learn about new ones and fun ways to use color palettes
• The statistics behind differential analysis packages
• ChIP-seq, ATAC-seq, single cell analysis methods
• Anything that will make data processing more efficient and user friendly

I am a graduate student who was originally trained as a bench scientist in the Hertel lab. In recent years, I have attended Data Science Initiative and GHTF sponsored workshops in an attempt to one day be able to analyze my own RNA-seq data. I credit a 7-week bioinformatics internship at the NCGR with helping me build a strong enough foundation to finally reach those "aha!" moments in my journey. I'd love to evolve my current strategy of "Learn from Google" into "Learn with others. ..and Learn from Google". I hope this group will create a supportive network where we can learn together, and from each other, as we build and expand our foundations in bioinformatics.

Cheers to a future of self sufficiency in bioinformatic analyses!

Current projects: RNA-seq analysis (human transcriptomics)

Interested in learning:

• Anything anyone is willing to share!
• ChiP-seq, eClip, parallelization, building pipelines, cool R plots, biostatistics, ERCC spike in normalization strategies