Data Analysis Team Ongoing Projects — Edge and Motif Analysis

[bklein7]

The purpose of this issue is to provide a forum for discussion and status updates regarding ongoing GRNmap Data Analysis Team projects.

At present, the following projects have been proposed for Spring 2018:

@maggie-oneil:

• [ ] Systematic analysis of edges in db5 through deletion of individual regulatory relationships

@bklein7:

• [ ] Extension of the previous multiple regression analysis (#330) to assess the 3 best, 3 middle, and 3 worst db5-derived random networks
• [ ] (Tentative) Systematic identification of motifs in db1-db6 and comparison to motifs in db5-derived random networks (Reference: http://younglab.wi.mit.edu/cgi-bin/young_public/navframe.cgi?s=17&f=network-analysis
• [ ] Investigate biological implications of db1-db6 based on known molecular mechanisms of the included TFs and associated motifs
• [ ] Based on the literature, consider what stressors might be best to apply to which specific yeast deletion strains for future (week 7) multiple stressors experiments

@lkelly9:

• [ ] Obtain access to the https://github.com/kdahlquist/DahlquistLab repository
• [ ] Work with @maggie-oneil and @bklein7 to collaborate on the above projects and learn more about the research performed by the GRNmap Data Analysis Team

To the above: please add to this task list as you see fit.

[bklein7]

January 19 Meeting Notes:

• Use missing data workbooks with the beta code for GRNmap at this time. Be sure to pass the same version of the beta code to all computers that runs will be performed on.
• Add Readme.md files for all new folders and copy over metadata template from Spring 2018 folder. Will help with version control.

[maggie-oneil]

This week @lkelly9 and I will be working on creating input workbooks for the db5 edge deletion experiments, and I will begin by running the models over the weekend, and @lkelly9 and I will be starting a write-up of the results next week, to be analyzed in later weeks.

We will be running the "intact" missing data workbook for db5 using the current (January 19, 2018) version of the GRNmap beta code. This "intact" db5 workbook was used to create 28 workbooks, the naming scheme and nature of which can be found in this README.md file https://github.com/kdahlquist/DahlquistLab/blob/master/data/Spring2018/MO.LK%20Edge%20Deletion%20Data/Edge%20Deletion%20Runs/README.md

The body of work that will be produced for this project can be found in the following folder: https://github.com/kdahlquist/DahlquistLab/tree/master/data/Spring2018/MO.LK%20Edge%20Deletion%20Data/Edge%20Deletion%20Runs

Specific data and presentations for future meetings will be updated and continued in this issue thread

[maggie-oneil]

Started running all models on paradoxus (15 models) and cerevisiae (14 models) using the protocol described by @bengfitzpatrick in https://github.com/kdahlquist/GRNmap/issues/391. I will check and start analysis of the model runs tomorrow, and will present initial findings during research meeting on Friday morning

[maggie-oneil]

All initial findings show that the models ran beautifully, and further analysis will be done during the research period this afternoon

[maggie-oneil]

This week Lauren and I ran 28 iterations of GRNmap to conduct an edge deletion analysis, and also ran the generated output workbooks through Gephi. Below is the compiled statistics from these runs. We will be using this document to look at significance of edges in future weeks, with an updated version of the document and the model runs with meta-data to be uploaded next week

https://github.com/kdahlquist/DahlquistLab/blob/master/data/Spring2018/MO.LK%20Edge%20Deletion%20Data/Edge%20Deletion%20Runs/Edge%20Analysis%20Master%20File.xlsx

[bklein7]

This week, I completed the multiple regression analysis of the 3 best and worst performing db5-derived random networks. All relevant documents are stored in a new multiple regression (MR) folder within the Dahlquist Lab repository: https://github.com/kdahlquist/DahlquistLab/tree/master/data/Spring2018/random_networks_analysis/multiple_regression_analysis.

MSE:minMSE data for this analysis was obtained from previous work by Natalie: https://github.com/kdahlquist/DahlquistLab/blob/master/data/Spring2017/15-gene_networks_analysis/MSE_minMSE_analysis/MSE-ratios_rand7-12-15-16-24-31_NEW.xlsx.

Gephi graph statistics for the random networks were obtained from the following folder: https://github.com/kdahlquist/DahlquistLab/tree/master/data/Spring2017/Gephi_output/Gephi_db5-derived-random-network-1-through-31_output/GraphML_output_files. The values corresponding to the 3 best and worst performing random networks were then compiled into a new document here: https://github.com/kdahlquist/DahlquistLab/blob/master/data/Spring2018/random_networks_analysis/multiple_regression_analysis/rand7-12-15-16-24-31_compiled-Gephi-stats_BK20180123.xlsx.

Optimized p & b values were obtained from the random network output sheets found here: https://github.com/kdahlquist/DahlquistLab/tree/master/data/Spring2017/bouldardii2_GRNmap_inputs_outputs/GRNmap_db5-derived-random-network-1-through-31_input_output. The values corresponding to the 3 best and worst performing random networks were then compiled into a new document here: https://github.com/kdahlquist/DahlquistLab/blob/master/data/Spring2018/random_networks_analysis/multiple_regression_analysis/rand7-12-15-16-24-31_compiled-optimized-p%26b_BK20180123.xlsx.

The input sheets for SPSS containing all dependent and independent variables for the 3 best and worst performing random networks was uploaded to the MR folder: https://github.com/kdahlquist/DahlquistLab/blob/master/data/Spring2018/random_networks_analysis/multiple_regression_analysis/rand7-12-15-16-24-31_multiple-regression-analysis_BK20180123.xlsx.

All SPSS outputs and screenshots of important regression models were uploaded to the MR folder (https://github.com/kdahlquist/DahlquistLab/tree/master/data/Spring2018/random_networks_analysis/multiple_regression_analysis).

Finally, the results were compiled in the following PowerPoint presentation: https://github.com/kdahlquist/DahlquistLab/blob/master/data/Spring2018/random_networks_analysis/multiple_regression_analysis/rand-regression-analysis-notes_BK20180123.pptx. I have been working on a parallel Word document containing interpretations of the results, which I will upload with comments form lab meeting (2/2) and then upload to the MR folder.

[bengfitzpatrick]

@bengfitzpatrick and @kdahlquist ereview slides from @bklein7

[maggie-oneil]

Here is the presentation that @lkelly9 and I generated for this week regarding the db5 edge deletion runs. Still trying to figure out exactly what methods were involved in minMSE calculations, but those will be investigated next week. https://github.com/kdahlquist/DahlquistLab/blob/master/data/Spring2018/MO.LK%20Edge%20Deletion%20Data/Edge%20Deletion%20Runs/Analyzing%20the%20Results%20of%20the%20db5%20Edge-Deletion%20Experiment.pptx

[maggie-oneil]

The link to the last file, when opened on my computer said a file was corrupted so here is the document in google slides: https://docs.google.com/presentation/d/1zxsDW8J08eFn7hlKaiUUCfEhVuknX59WONApMd3PO7o/edit?usp=sharing

[bklein7]

A preliminary analysis of conserved network motifs in db1-db6 has been uploaded here: https://github.com/kdahlquist/DahlquistLab/blob/master/data/Spring2018/db1-db6_motif_analysis/db1-db6_motif-analysis_BK20180208.pptx.

The excel file containing the motif adjacency matrices input into GRNsight can be found here: https://github.com/kdahlquist/DahlquistLab/blob/master/data/Spring2018/db1-db6_motif_analysis/db1-db6_motif-analysis_BK20180208.xlsx.

[maggie-oneil]

This week I created a workbook that calculates MSE:minMSE ratios for the user. The complete version of the file has not been uploaded, but here is what is built so far. Further analysis of these values will be performed next week using the same paired t-test comparison as used for other analyses, and a readme file will be created, along with a blank template of the workbook for future use.

https://github.com/kdahlquist/DahlquistLab/blob/master/data/Spring2018/MO.LK%20Edge%20Deletion%20Data/Edge%20Deletion%20Runs/Analysis%20of%20Edge%20Deletion%20Runs/minMSE%20Master%20.xlsx

[maggie-oneil]

This week Lauren and I worked to update our edge deletion analysis to include the MSE:minMSE data, along with an analysis of how the edge weights were being modeled.

https://github.com/kdahlquist/DahlquistLab/blob/master/data/Spring2018/MO.LK%20Edge%20Deletion%20Data/Edge%20Deletion%20Runs/Analysis%20of%20Edge%20Deletion%20Runs/Analyzing%20the%20Results%20of%20the%20db5%20Edge-Deletion%20Experiment%20(1).pptx

[bklein7]

This week, I expanded the motif analysis, building up towards a 15-gene hypothesis network that synthesized findings from db1-db6 (which was systematically analyzed in my thesis discussion section).

PPT presentation: https://github.com/kdahlquist/DahlquistLab/blob/master/data/Spring2018/db1-db6_motif_analysis/db1-db6_motif-analysis_BK20180208.pptx.

Excel file: https://github.com/kdahlquist/DahlquistLab/blob/master/data/Spring2018/db1-db6_motif_analysis/db1-db6_motif-analysis_BK20180208.xlsx.

[lkelly9]

This week, Maggie and I organized possible figures for my poster.

Link to PPT: https://docs.google.com/presentation/d/1UmhFhMssNe3YISqxLWYcJ2un1sWBwO9jkzXpcHKf-hQ/edit?ts=5a98a430#slide=id.g312908c8ea_0_75

[bengfitzpatrick]

Time course plots for the targets of deleted edges having big decrease impact on LSE: hmo1->cin5 hmo1->yox1 msn2->yox1 zap1->ace2

Plot log2 fold change vs time (from excel optimized expression model) for the db5 and the deleted gene model fit and the mean ("data" data) log 2 fold change on single set of axes for each of the three target genes above..

Tie in these plots to the heat map of activation/repression. Lots of moving parts to connect here... GoT.

Try some MSE minMSE visualizations to see what might work in poster.

[maggie-oneil]

https://github.com/kdahlquist/DahlquistLab/blob/master/data/Spring2018/MO.LK%20Edge%20Deletion%20Data/Edge%20Deletion%20Runs/Analysis%20of%20Edge%20Deletion%20Runs/LK%20Figures.pptx

A ppt version of the poster figures can be found here. @lkelly9 still needs access/permission to access the Dahlquist Lab repository

[kdahlquist]

Invited @lkelly9 to DahlquistLab repository. She now needs to accept. Sorry for the oversight.

[lkelly9]

Weighted Graphs.pptx Currently working on compiling all of our figures/data into a powerpoint. This is what I have so far.

[lkelly9]

Weighted Graphs (1).pptx

More compiling of figures/data into a powerpoint

[bengfitzpatrick]

Lauren compiled graphs and tables into ppt above. @bengfitzpatrick will review.

[lkelly9]

Weighted Graphs (2).pptx Added graphs for optimized gene expression and the weighted graphs with the asterisks indicating which edge weights changed as a result of the deletion.

[bklein7]

@lkelly9 : You can find the consolidated network input & output sheets here: https://github.com/kdahlquist/DahlquistLab/tree/master/data/Spring2018/consolidated-network.

It would be great if you could run this network in Gephi next week!

[lkelly9]

BKconsolidatednetwork_excelformat (1).xlsx

@bklein7 I had to save it as another format to get it to upload, let me know if this works