Aporras1 Individual Assessment and Reflection

User page: Antonio Porras

Assignment page: Deliverables Page

Group page: JASPAR the Friendly Ghost

Individual Assessment and Reflection

Statement of Work

1. Describe exactly what you did on the project.

As data analyst I was responsible for performing statistical analysis on dZAP1 expression data provided by Dr. Dahlquist's lab. During Week 8 I completed the ANOVA test along with calculating Benjamini-Hochberg corrected p value and the Bonferroni-corrected p-value. The first calculation was less stringent compared to the Bonferroni but both were useful in terms of improving the confidence in the data. The precise steps and outline of what I completed can be found in my Aporras1_Week_8 journal.

Moving into Week 10, I performed STEM high level analysis on the ANOVA data in order to generate gene clusters which presented similar expression over the course of the experiment. Seven significant clusters were generated and the GOlists & genelists were saved and uploaded to the wiki for later analysis. I read and interpreted 6 GOlist terms found in the GOlist of Profile 22 and attempted to understand why the cell would be changing expression in genes associated with certain cell processes. The precise steps and outline of what I completed can be found in my Aporras1_Week_10 journal.

In Week 11, I worked alongside Quinn Lanners to perform a literature search on yeast and cold shock to gain brief exposure to journal articles in this area of research and search engine qualities. The precise steps and outline can be found in my Aporras1_Week_11 journal. The following week Quinn Lanners and I did more in-depth research on the specific journal article: Genome-wide analysis of the yeast transcriptome upon heat and cold shock (Becerra et al., 2003). We outlined the introduction, methods, procedure, analysis tools, and overall findings of the article before creating and presenting a presentation to the class which can be found in my Aporras1_Week_12 journal along with the specific outline and approach to interpretation of their data.

In Week 14 and Week 15 I continued work from the Week 10 data analysis and selected profile 22 of dZAP1 from STEM analysis. I then generated a list of significant transcription factors which targeted genes within the genelist provided by STEM and further used those transcription factors to create a regulatory network. This network was actually determined to be too large and Dr. Dahlquist trimmed down the network to 15 transcription factors. The network was then put into GRNsight to visualize the regulation pathways. MATLAB was also used to generate an output which would allow for GRNsight to display the direction of regulation and the magnitude with colors and bold/thin regulation arrows. A more detailed outline for the process can be found in my Aporras1_Week_14 journal.

Once I completed all the analysis, I then put the data onto the deliverables page, presentation, and the final paper along with my analysis. These files can be found in JASPAR_the_Friendly_Ghost_Final_Deliverables. I was primarily responsible for maintaining extreme care with the files and keeping a very well-kept record of data. In addition I worked closely with Quinn Lanners to complete the final paper and aid in any way possible once I completed my data calculations and subsequent analysis. A more detailed outline for the process can be found in my Aporras1_Week_15 journal.

Assessment of Project

2. Give an objective assessment of the success of your project workflow and teamwork.

I would say the overall project workflow and teamwork was fairly cohesive considering our different academic backgrounds and schedules. Given this time of the year, with final exams, we did very well to meet outside of class and work in the lab while communicating constantly. My workflow didn't impede the workflow of anyone else throughout the project and it was definitely a good feeling to have throughout working on the project as I attempted to complete everything ahead of time and work on group deliverables before my own.

3. What worked and what didn't work?

What didn't work was, or at least I didn't fully accept, was the need for both a paper and a presentation. I felt as though it became repetitive when examining both the paper and the introduction. With regards to the team, there weren't any aspects that didn't work, except I wish I would have had a better understanding of the role of the coders and their work through JASPAR. It took a lot of curiosity and asking to figure it out rather than being explained it in the beginning.

4. What would you do differently if you could do it all over again?

I definitely wish I had the same good data record keeping skills that I have currently because it would have saved a lot of time throughout the semester.

5. Evaluate your team’s portion of the GRNsight Gene Page Project and Group Report in the following areas:

* Content: What is the quality of the work?

From my understanding of the coders, they put their best foot forward in terms of working in a new area in which they hadn't worked in before. As data analyst I had context and prior understanding of my analysis but for them they had to work with a completely new database, JASPAR. Quinn created a structure by which every aspect was planned out and made it easy to keep track of deadlines and goals. Overall, while also considering the amount of time spent throughout these last few weeks and paying attention to very specific details, JASPAR the Friendly Ghost did their best to complete what was assigned. Again, while paying attention to copious details.

* Organization: Comment on the organization of the project and of your group's wiki pages.

As I mentioned earlier, Quinn structured the page easily so that even I could go ahead and add sections because we all understood the intuitive layout. I kept detailed file records and explained any changes I made to the data while also maintaining a detailed electronic notebook every single week.

* Completeness: Did your team achieve all of the project objectives? Why or why not?

To the best of my knowledge, we did. We would go through the deliverables page line by line checking tasks off in order to ensure that our product was as complete as it could be. Of course its not perfect, but considering the amount of details and time given, we put a significant amount of time into the project and displaying documentation throughout.

Reflection on the Process

What did you learn?

With your head (biological or computer science principles)

I definitely have much better data management than I did at the beginning of the course and the ability to organize thoughts for someone else to read and replicate the processes I completed throughout the semester. Ultimately, synthesizing replicable data and thus very detailed step by step notes. In terms of biology I didn't take as much because we didn't go very much in depth but now I have a better understanding of how to interpret more intricate data sets and understand the context at least in respect to microarray data.

With your heart (personal qualities and teamwork qualities that make things work or not work)?

Simply working hard.. and early! It made a huge difference in my workflow to finish assignments ahead of time (prior journal entries may not display this). Instead of waiting for deadlines I found an ethic to attack them to account for time where I was met with difficulties or setbacks (e.g. having to trim down my regulation network) and these setbacks didn't do as much damage because I met them so early before the deadline.

With your hands (technical skills)?

I've been around computers for a very long time so I didn't really gain any technical skills besides knowing how I work best. I came to the lab because the screens were bigger and I usually used two monitors to save time going in between the assignment Page, individual page, and datasets. This greatly improved my workflow and provided structure which I thrive from.

What lesson will you take away from this project that you will still use a year from now?

Recognizing how I work best. As soon as I recognized how I work best (e.g. working with multiple monitors or working on assignments early) I was able to improve my efficiency as the assignments got more difficult. Lastly, data management and organization. Organization with respect to files made the process much easier than if I hadn't learned to be descriptive with file names or have multiple backups and a notepad with a filename and description. These organizational techniques were vital and will be useful in future environments where data is often more digital than it is paper.

Aporras1 (talk) 16:18, 15 December 2017 (PST)

Acknowledgements

1. Copied the structure of the sections in my assessment and reflection from the Deliverables Page.
2. Worked alongside Quinn Lanners in Week 11 and 12 and subsequently Weeks 14 and 15 to complete the assignment.
3. The JASPAR the Friendly Ghost team members including Quinn Lanners, Simon Wroblewski, and Eddie Bachoura.
4. Received assistance in completing the assignments from Dr. Dahlquist and Dr. Dionisio.
5. The entire class members who I had the opportunity to work alongside.
6. LMU Biology and Computer Science Departments for the resources throughout the semester.

While I worked with the people noted above, this individual journal entry was completed by me and not copied from another source.

Aporras1 (talk) 16:00, 15 December 2017 (PST)

References

1. Dahlquist, K. D., Dionisio, J. D. N., Fitzpatrick, B. G., Anguiano, N. A., Varshneya, A., Southwick, B. J., & Samdarshi, M. (2016). GRNsight: a web application and service for visualizing models of small-to medium-scale gene regulatory networks. PeerJ Computer Science, 2, e85.
2. LMU BioDB 2017. (2017). GRNsight Gene Page Project Deliverables. Retrieved December 15, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/GRNsight_Gene_Page_Project_Deliverables
3. LMU BioDB 2017. (2017). Aporras1 Week 8. Retrieved December 15, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Aporras1_Week_8
4. LMU BioDB 2017. (2017). Aporras1 Week 10. Retrieved December 15, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Aporras1_Week_10
5. LMU BioDB 2017. (2017). Aporras1 Week 11. Retrieved December 15, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Aporras1_Week_11
6. LMU BioDB 2017. (2017). Aporras1 Week 12. Retrieved December 15, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Aporras1_Week_12
7. LMU BioDB 2017. (2017). Aporras1 Week 14. Retrieved December 15, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Aporras1_Week_14
8. LMU BioDB 2017. (2017). Aporras1 Week 15. Retrieved December 15, 2017, from https://xmlpipedb.cs.lmu.edu/biodb/fall2017/index.php/Aporras1_Week_15
9. Teixeira, M. C., Monteiro, P. T., Guerreiro, J. F., Gonçalves, J. P., Mira, N. P., dos Santos, S. C., ... & Madeira, S. C. (2013). The YEASTRACT database: an upgraded information system for the analysis of gene and genomic transcription regulation in Saccharomyces cerevisiae. Nucleic acids research, 42(D1), D161-D166.