Ckaplan Week 10

Media: BIOL367_S24_microarray-data_dGLN3CKAS31211.xlsx

Media:Updated_Pvalues_ckaplan.pdf

Media:Andrew&Charlotte_Tables_Gene-GoData.zip

Media:AS&CK_BIOL367_S24_STEM_PHOTOS_dGLN3.pptx

Media:Yeastract_45_Gene_CK.xlsx

Media:GRN_(Yeastmine_-_SGD__2024-03-19;_13_genes,_21_edges)_weighted_(2)_ck_45.xlsx

Media:CKgenegraph.jpg

Procedure:

Prepare Microarray Data for STEM: I created a new worksheet named "dGln3_stem" in Excel. I copied data from the "dGln3_ANOVA" worksheet and pasted values into "dGln3_stem". I renamed columns: "Master_Index" to "SPOT", "ID" to "Gene Symbol", and deleted the column "Standard_Name". I filtered data on the B-H corrected p value (> 0.05), deleted irrelevant rows, and retained only significant gene expression changes. I deleted unnecessary columns, leaving only Average Log Fold Change columns for each time point and renamed them. I removed #DIV/0! errors. I saved the spreadsheet as Text (Tab-delimited) (*.txt) after turning on file extensions. Setting up STEM: I downloaded and extracted the STEM software. I downloaded the Gene Ontology and yeast GO annotations files and placed them in the STEM folder. I launched STEM by double-clicking on stem.jar. In the main STEM interface, I configured settings in sections 1 to 4 as instructed. I ran STEM by clicking the Execute button. Viewing and Saving STEM Results: I reviewed the generated STEM Profiles. I adjusted the X-axis scale to "Based on real time". I took screenshots of significant profiles and saved them in a PowerPoint presentation. I saved gene lists and GO term lists for significant profiles as instructed. Analyzing STEM Results: I chose a significant profile with a clear cold shock/recovery pattern. I examined the number of genes belonging to the profile and the p value for enrichment of genes. I filtered GO terms based on p values and selected 6 significant terms for further analysis. I looked up definitions of selected GO terms on the Gene Ontology website. Using YEASTRACT: I copied gene IDs from the chosen profile in Excel. I visited the YEASTRACT database and pasted the gene list. I ranked genes by TF and noted significant transcription factors. Creating and Visualizing Gene Regulatory Network with GRNsight: I selected transcription factors from YEASTRACT results, including GLN3. I loaded the network in GRNsight, ensuring connectivity. I recorded the number of genes and edges. I exported the network image as a PNG and uploaded it to the wiki. Creating GRNmap Input Workbook: I exported data from GRNsight to Excel. I checked sheets for correctness, ensuring adjacency matrix, log2 fold changes, and other parameters. I inserted a new worksheet named "network_weights" and copied the network data. I adjusted optimization parameters as instructed. I saved and uploaded the Excel Workbook to the wiki.

• Why did you select this profile? In other words, why was it interesting to you?===

I selected profile 45 because I thought it was interesting because out of all off our profiles, it had the most genes.

• How many genes belong to this profile?===

406

• How many genes were expected to belong to this profile?===

29.9

• What is the p value for the enrichment of genes in this profile?===

0.00

I have 44 green genes

Gln3p 46.65% Cin5p 31.27%

Assignment Pages

• Week 1
• Week 2
• Week 3
• Week 4
• Week 5
• Week 6
• Week 8
• Week 9
• Week 10
• Week 11
• Week 12
• Week 13
• Week 14
• Week 15

Individual Journal Entry Pages

• ckaplan Week 1
• ckaplan Week 2
• SIR2 Week 3
• AgeAnnoMO Week 4
• ckaplan Week 5
• ckaplan Week 6
• ckaplan Week 8
• ckaplan Week 9
• ckaplan Week 10
• ckaplan Week 11
• ckaplan Week 12
• ckaplan Week 13
• ckaplan Week 14
• ckaplan Week 15

Shared Journal Entry Pages

• Class Journal Week 1
• Class Journal Week 2
• Class Journal Week 3
• Class Journal Week 4
• Class Journal Week 5
• Class Journal Week 6
• Class Journal Week 8
• Class Journal Week 9
• Class Journal Week 10