Ckaplan Week 10

Purpose:

This assignment helps us learn microarray data analysis and gene analysis techniques. It also provides practice in determining p-values and organizing data effectively.

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.

Methods/Results:

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

• 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%

Acknowledgments

I worked with Andrew in and out of class. Dr. Dahlquist assisted us in class.

References

Dahlquist, K. Master_sheet_dGLN3. LMU BioDB 2024. (2024). Week 9. Retrieved Mar 20, 2024, from https://xmlpipedb.cs.lmu.edu/biodb/Spring2024/index.php/Week_9 LMU BioDB 2024. (2024). Week 9. Retrieved Mar 31, 2024, from https://xmlpipedb.cs.lmu.edu/biodb/spring2024/index.php/Week_10

Assignment Pages

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