Notes 2/25/16 - Revision history

Ktsmith at 18:45, 8 March 2016

2016-03-08T18:45:53Z

Ktsmith at 19:56, 25 February 2016

2016-02-25T19:56:39Z

Ktsmith at 19:56, 25 February 2016

2016-02-25T19:56:06Z

Ktsmith at 19:28, 25 February 2016

2016-02-25T19:28:31Z

Ktsmith at 19:27, 25 February 2016

2016-02-25T19:27:07Z

Ktsmith at 19:26, 25 February 2016

2016-02-25T19:26:57Z

Ktsmith: Created page with "Last class we realized that the fed and not fed were not clustering correctly Could possibly get them to cluster by filtering out extremely high values or change the correla..."

2016-02-25T18:52:01Z

Created page with "Last class we realized that the fed and not fed were not clustering correctly Could possibly get them to cluster by filtering out extremely high values or change the correla..."

New page

Last class we realized that the fed and not fed were not clustering correctly

Could possibly get them to cluster by filtering out extremely high values or change the correlation for FPKM. However, Dr. Heyer pointed out that we already found genes that had differential expression among the two groups so clustering doesn't matter too much. Will still be important to try to fix however for the pictures that we will use.

Today we will continue to look for genes. Look mainly at genes that are transcription factors or kinases, things that could be in charge of amplification of the cycle to cause cell growth (List of these genes on google doc)

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 '''New Direction'''
-Decided to use correlation clustering to find a list of genes and try to get the clusters to be correct. Decided to get rid of values of 5000 then used correlation clustering. Saved the list of genes that came from correlation into a file. will use these later to do supervised clustering. (Heat map using correlation clustering below)
+Decided to use correlation clustering to find a list of genes and try to get the clusters to be correct. Decided to get rid of values of 5000 then used correlation clustering. This finds genes that are differentially expressed among the two groups then finds genes that are correlated to each other. Saved the list of genes that came from correlation into a file. Will look at these genes for any genes that really stand out as great candidate genes. Will use these later to do supervised clustering. (Heat map using correlation clustering below)
 [[File:Screen_Shot_2016-02-25_at_2.53.50_PM.png]]

← Older revision		Revision as of 19:56, 25 February 2016
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	Decided to use correlation clustering to find a list of genes and try to get the clusters to be correct. Decided to get rid of values of 5000 then used correlation clustering. Saved the list of genes that came from correlation into a file. will use these later to do supervised clustering. (Heat map using correlation clustering below)		Decided to use correlation clustering to find a list of genes and try to get the clusters to be correct. Decided to get rid of values of 5000 then used correlation clustering. Saved the list of genes that came from correlation into a file. will use these later to do supervised clustering. (Heat map using correlation clustering below)
		+
		+	[[File:Screen_Shot_2016-02-25_at_2.53.50_PM.png]]

← Older revision		Revision as of 19:56, 25 February 2016
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	[[File:Not_correct_clustering.png‎]]		[[File:Not_correct_clustering.png‎]]
		+
		+
		+	'''New Direction'''
		+
		+	Decided to use correlation clustering to find a list of genes and try to get the clusters to be correct. Decided to get rid of values of 5000 then used correlation clustering. Saved the list of genes that came from correlation into a file. will use these later to do supervised clustering. (Heat map using correlation clustering below)

@@ Line 2: / Line 2: @@
 Could possibly get them to cluster by filtering out extremely high values or change the correlation for FPKM. However, Dr. Heyer pointed out that we already found genes that had differential expression among the two groups so clustering doesn't matter too much. Will still be important to try to fix however for the pictures that we will use.
 Today we will continue to look for genes. Look mainly at genes that are transcription factors or kinases, things that could be in charge of amplification of the cycle to cause cell growth (List of these genes on google doc)
-Wrote deOut to a file, but was not able to understand exactly what it was saying. Saw some differential expression but the numbers were pretty close to each other, assume the the program is working like it is supposed to.
+Because Dr. Heyer said that the genes were already separated among the two groups I decided to write deOut to a file to see the data with the hopes that i would be able to clearly see that fed and not fed were different from each other, but was not able to understand exactly what it was saying. Saw some differential expression but the numbers were pretty close to each other, assume the the program is working like it is supposed to.
-Dr. Campbell told us to remove mean values that were greater than 8000. This allows us to correlate genes better. However still not able to cluster fed and not fed with each other (example below using Contig8459_SVS1_Protein_SVS1_Saccharomyces_cerevisiae_strain_ATCC_204508_/_S288c gene
+Dr. Campbell told us to remove mean expression values that were greater than 8000. This allows us to correlate genes better. However still not able to cluster fed and not fed with each other (example below using Contig8459_SVS1_Protein_SVS1_Saccharomyces_cerevisiae_strain_ATCC_204508_/_S288c gene
 [[File:Not_correct_clustering.png‎]]

← Older revision		Revision as of 19:27, 25 February 2016
Line 9:		Line 9:

	Dr. Campbell told us to remove mean values that were greater than 8000. This allows us to correlate genes better. However still not able to cluster fed and not fed with each other (example below using Contig8459_SVS1_Protein_SVS1_Saccharomyces_cerevisiae_strain_ATCC_204508_/_S288c gene		Dr. Campbell told us to remove mean values that were greater than 8000. This allows us to correlate genes better. However still not able to cluster fed and not fed with each other (example below using Contig8459_SVS1_Protein_SVS1_Saccharomyces_cerevisiae_strain_ATCC_204508_/_S288c gene
		+
	[[File:Not_correct_clustering.png‎]]		[[File:Not_correct_clustering.png‎]]

← Older revision		Revision as of 19:26, 25 February 2016
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	Today we will continue to look for genes. Look mainly at genes that are transcription factors or kinases, things that could be in charge of amplification of the cycle to cause cell growth (List of these genes on google doc)		Today we will continue to look for genes. Look mainly at genes that are transcription factors or kinases, things that could be in charge of amplification of the cycle to cause cell growth (List of these genes on google doc)
		+
		+	Wrote deOut to a file, but was not able to understand exactly what it was saying. Saw some differential expression but the numbers were pretty close to each other, assume the the program is working like it is supposed to.
		+
		+	Dr. Campbell told us to remove mean values that were greater than 8000. This allows us to correlate genes better. However still not able to cluster fed and not fed with each other (example below using Contig8459_SVS1_Protein_SVS1_Saccharomyces_cerevisiae_strain_ATCC_204508_/_S288c gene
		+	[[File:Not_correct_clustering.png‎]]