Class Journal Week 7 - Revision history

Ymesfin: /* Aby Mesfin's Response */ added signature

2019-10-17T23:03:49Z

‎Aby Mesfin's Response: added signature

Dramir36: /* David Ramirez's Response */ added signature

2019-10-17T06:56:04Z

‎David Ramirez's Response: added signature

Dramir36: /* David Ramirez's Response */ answered questions

2019-10-17T06:54:43Z

‎David Ramirez's Response: answered questions

Jcowan4: /* Do you have any further reaction to this case after viewing Dr. Baggerly's talk? */ signature

2019-10-17T05:50:06Z

‎Do you have any further reaction to this case after viewing Dr. Baggerly's talk?: signature

Jcowan4: /* Do you have any further reaction to this case after viewing Dr. Baggerly's talk? */ response

2019-10-17T05:49:42Z

‎Do you have any further reaction to this case after viewing Dr. Baggerly's talk?: response

Jcowan4: /* What best practices did you perform for this week's assignment? */ responded

2019-10-17T05:44:37Z

‎What best practices did you perform for this week's assignment?: responded

Jcowan4: Responded to question

2019-10-17T05:37:53Z

Responded to question

Jcowan4: answered question

2019-10-17T05:22:31Z

answered question

Eyoung20: /* Emma Young's Response */ added response to fourth question and my signature

2019-10-17T05:00:12Z

‎Emma Young's Response: added response to fourth question and my signature

Dmadere: /* DeLisa Madere's Response */ invoked template

2019-10-17T04:59:28Z

‎DeLisa Madere's Response: invoked template

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 ===Do you have any further reaction to this case after viewing Dr. Baggerly's talk?===
 I appreciated how this video broke down the bioinformatics and data sharing that went behind discovering the fraudulence of Potti's research. It helped me better understand the mechanisms that went into this discovery while also underlining the value of reproducibility in research.
 ==Christina Dominguez's Response==

← Older revision		Revision as of 06:56, 17 October 2019
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	:The talk brought up point of how Duke University said that they have become more confident into evolving the personalized cancer treatment, which seems really odd. I would have thought that Duke would have taken some time off of cancer research, but have instead become more encouraged to continue the cancer research.		:The talk brought up point of how Duke University said that they have become more confident into evolving the personalized cancer treatment, which seems really odd. I would have thought that Duke would have taken some time off of cancer research, but have instead become more encouraged to continue the cancer research.
		+	[[User:Dramir36\|Dramir36]] ([[User talk:Dramir36\|talk]]) 23:56, 16 October 2019 (PDT)

	==Jonar Cowan's Response==		==Jonar Cowan's Response==

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 '''1. What were the main issues with the data and analysis identified by Baggerly and Coombs? What best practices enumerated by DataONE were violated? Which of these did Dr. Baggerly claim were common issues?
-:The first issue mentioned was
+:The first issue mentioned was that there was an off-by-one indexing error for all of the genes in the signature. This may have happened through the software that was used. Another issue was that the software also gave predictions. Not all heatmaps were labeled correctly. Transferring data from excel to another data software can cause error. When predictions were made for Adriamycin, the data portrayed that the drug was resistant for most patients, but in actuality, is very effective. The best practices that were violated are that the columns of data were not kept consistent during data transfer from one software to the other. It also seems that the data was not stored in a format that could be used by any application, which would have prevented incorrect data analysis by the software used. Dr. Baggerly claimed that change in the data sets between data transfer of software is a very common issue.
 '''2. What recommendations does Dr. Baggerly recommend for reproducible research? How do these correspond to what DataONE recommends?
+:The recommendation is that the data process should be transparent and reproducible during the integration process. As Dr. Baggerly stated, reproducible data should be accessible to any person so that they are able to read the paper and reports that contain all the code so that proof can be shown for the data results. This implies, from DataONE, that others should be able to understand and can evaluate the person's decision making process.
 '''3. What best practices did you perform for this week's assignment?
-'''4. Do you have any further reaction to this case after viewing Dr. Baggerly's talk?
+:The talk brought up point of how Duke University said that they have become more confident into evolving the personalized cancer treatment, which seems really odd. I would have thought that Duke would have taken some time off of cancer research, but have instead become more encouraged to continue the cancer research.
 ==Jonar Cowan's Response==

← Older revision		Revision as of 05:50, 17 October 2019
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	{{jcowan4}}		{{jcowan4}}
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		+	[[User:Jcowan4\|Jcowan4]] ([[User talk:Jcowan4\|talk]]) 22:50, 16 October 2019 (PDT)

	==Emma Young's Response==		==Emma Young's Response==

← Older revision		Revision as of 05:49, 17 October 2019
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	===Do you have any further reaction to this case after viewing Dr. Baggerly's talk?===		===Do you have any further reaction to this case after viewing Dr. Baggerly's talk?===

		+	In regards to Potti's work, I am shocked at how long the process took for Potti's work to be disproved. At the same time, I thought that with all the regulations and practices in the scientific field, we would not run into such a problem with false data.

	{{jcowan4}}		{{jcowan4}}

← Older revision		Revision as of 05:44, 17 October 2019
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	===What best practices did you perform for this week's assignment?===		===What best practices did you perform for this week's assignment?===
		+
		+	:For this weeks assignment, I practiced proper labeling of data and using the same applications and files.

	===Do you have any further reaction to this case after viewing Dr. Baggerly's talk?===		===Do you have any further reaction to this case after viewing Dr. Baggerly's talk?===

← Older revision		Revision as of 05:37, 17 October 2019
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	===What recommendations does Dr. Baggerly recommend for reproducible research? How do these correspond to what DataONE recommends?===		===What recommendations does Dr. Baggerly recommend for reproducible research? How do these correspond to what DataONE recommends?===
		+
		+	Dr. Baggerly suggests that consistency with reusing templates and labeling, as well as having a report of the whole process in detail is important for reproducible data. DataONE recommends properly labeled data (columns and any data entry) and proper long term storage, essentially they are promoting the same advice.

	===What best practices did you perform for this week's assignment?===		===What best practices did you perform for this week's assignment?===

← Older revision		Revision as of 05:22, 17 October 2019
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	===What were the main issues with the data and analysis identified by Baggerly and Coombs? What best practices enumerated by DataONE were violated? Which of these did Dr. Baggerly claim were common issues?===		===What were the main issues with the data and analysis identified by Baggerly and Coombs? What best practices enumerated by DataONE were violated? Which of these did Dr. Baggerly claim were common issues?===
		+
		+	The main issues revolved around the inconsistency of data, lack of proper labeling and instructions. Baggerly and Coombs showed that data replication was inconsistent and repeating the process brought inconsistent results. There was also mention of data being read incorrectly, which resulted in misunderstanding. DataONE suggests labeling is an important practice to create reproducible data. Common issues would be mislabeling data.

	===What recommendations does Dr. Baggerly recommend for reproducible research? How do these correspond to what DataONE recommends?===		===What recommendations does Dr. Baggerly recommend for reproducible research? How do these correspond to what DataONE recommends?===

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 #* In this weeks assignments we have used the best practices of labeling our data with distinct and informative names, we are keeping all our data in one table, and we are keeping progressive saved files of our data analysis.
 #Do you have any further reaction to this case after viewing Dr. Baggerly's talk?
 {{Template: eyoung20}}

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 #*After hearing this talk, it seemed more so that the data presented was not complete at all and implied that the scientists behind the scandal knew this and wanted to give 50% of their effort into this experiment. The fact that the common issues with the data had to do with the labeling revealed that they were not being careful about even the most simple things including the labels.
 [[User:Dmadere|Dmadere]] ([[User talk:Dmadere|talk]]) 21:59, 16 October 2019 (PDT)
-{{Template}}
+{{Dmadere}}
 ==David Ramirez's Response==