Eyoung20 journal week 12/13
Milestone 1: Annotated Bibliography[edit] The Data Analysts will work with their teams to develop an annotated bibliography of papers relating to their team's assigned paper. Milestone 2: Journal Club Presentation[edit] The Data Analysts will work with their teams to create and deliver a Journal Club presentation about to their team's assigned paper. Milestone 3: Getting the data ready for analysis[edit] Download and examine the microarray dataset, comparing it to the samples and experiment described in your journal club article. Barreto et al. (2012) Kitagawa et al. (2002) Thorsen et al. (2007) Along with the QA's, make a "sample-data relationship table" that lists all of the samples (microarray chips), noting the treatment, time point, and replicate number. Come up with consistent column headers that summarize this information For example, the Dahlquist Lab microarray data used strain_LogFC_timepoint-replicate number, as in wt_LogFC_t15-1. Organize the data in a worksheet in an Excel workbook so that: ID is in the first column Data columns are to the right, in increasing chronological order, using the column header pattern you created Replicates are grouped together Milestone 4: ANOVA analysis[edit] Perform an ANOVA analysis of the data, as you did on Week 8 for the Dahlquist lab data. Note that you will need to adjust your formulas to take into account the different number of timepoints and replicates in your article's dataset. Milestone 5: Clustering with stem and YEASTRACT[edit] Cluster the data with stem, as you did on Week 9. Note that we will make some adjustments to the GO term analysis because stem was not providing GO term names. Use YEASTRACT to generate a candidate gene regulatory network as you did on Week 9. Milestone 6: Create an input workbook for GRNmap using MS Access database[edit] Create an input workbook for GRNmap based on a Microsoft Access database that the Coder/Designer and QA's make, following protocol in Week 10 Run GRNmap and interpret data. As the end-user of the Access database, the Data Analysts will provide feedback to the QAs and Coder/Designer about the usability of database.
