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.

Creating and Visualizing My Gene Regulatory Network with GRNsight: From profile 45, I selected transcription factors from the list of significant ones in YEASTRACT to build a gene regulatory network using GRNsight. I ensured that the network had approximately 15-20 connected transcription factors and exported the network image as a PNG file, uploading it to the wiki and displaying it on my individual journal page.

Creating the GRNmap Input Workbook: I exported data from GRNsight to Excel for generating the GRNmap input workbook. After exporting, I checked the workbook to ensure it included the required sheets with the specified content, such as the adjacency matrix in the "network" sheet and log2 fold changes in the expression sheets. Additionally, I adjusted the optimization parameters as instructed, created a new worksheet named "network_weights," and transferred the content of the "network" sheet to it. Finally, I saved the workbook, uploaded it to the wiki, and linked it to my individual journal page for further processing by Dr. Dahlquist in the GRNmap modeling software.

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 throughout the week. 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

• 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