--- tags: ggg, ggg2020, ggg298 --- # GGG 298 - Week 1 [toc] ## Wednesday Lab Outline - 1/8 * introductions (Titus, Shannon) * [syllabus](https://hackmd.io/3bDesjZaTVSiEzEueSGlDQ?view) * goals of this course * how this course will differ from GGG 201(b) * how this course will differ from other courses * [signing up for a farm account](https://github.com/dib-lab/dib_rotation/blob/master/01_farm_account.md) * auditing foo * BREAK * our data set & workflow: RNAseq in 15 minutes or less * [practical session](https://hackmd.io/kXHoB6g4R92OIOwoNR2vkg) - R for data analysis, RMarkdown for presentation of data analysis * thoughts and questions! ## Friday Discussion - 1/10 For this Friday, please skim [A preliminary review of influential works in data-driven discovery](https://springerplus.springeropen.com/articles/10.1186/s40064-016-2888-8), Stalzer & Mentzel, 2016. ## Homework for Week 2 (Due Friday 1/17 at 11am, entered into [this form](https://docs.google.com/forms/d/e/1FAIpQLSfYEV2hp3Ejl9qNpI_CX9th9uQgY_Un8S6Tnt2UHLlSogdBPQ/viewform).) Please re-read [A preliminary review of influential works in data-driven discovery](https://springerplus.springeropen.com/articles/10.1186/s40064-016-2888-8), Stalzer & Mentzel, 2016. Then, submit 3-4 sentences describing either a problem that you tackled with one of the techniques described in this paper, _or_ a problem that you _want_ to tackle.