Nick Rohacz: Summer 2011 Week 2: Difference between revisions
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===May 25, 2011=== | ===May 25, 2011=== | ||
Spent the morning trying to match up the Log Fold Changes before global normalization and after global normalization from the .gpr files. Ideally the graph should have a linear trend line if global normalization had subtracted the same constant from every spot. However, some of the files output a fuzzy region around the origin, this can be seen in the separate powerpoint with the graphs. The individual red/green intensities were graphed next. The normalized red intensities was graphed against the non-normalized red intensities and the same for the green intensities. These graphs should all be a linear line as well, however some awkward points occurred. The fuzzy region from the LogFC graph is thought to be a resultant from the "error" messages that are scattered throughout the .gpr files. These are a result of the intensity ratio being negative and the Log of any negative number does not exist. The number of "error" messages in each file seemed to correlate with the fuzzy section around the origin, as the number of "error"'s went up, the fuzziness increased to an extent were it almost was not linear anymore. | Spent the morning trying to match up the Log Fold Changes before global normalization and after global normalization from the .gpr files. Ideally the graph should have a linear trend line if global normalization had subtracted the same constant from every spot. However, some of the files output a fuzzy region around the origin, this can be seen in the separate powerpoint with the graphs. The individual red/green intensities were graphed next. The normalized red intensities was graphed against the non-normalized red intensities and the same for the green intensities. These graphs should all be a linear line as well, however some awkward points occurred. The fuzzy region from the LogFC graph is thought to be a resultant from the "error" messages that are scattered throughout the .gpr files. These are a result of the intensity ratio being negative and the Log of any negative number does not exist. The number of "error" messages in each file seemed to correlate with the fuzzy section around the origin, as the number of "error"'s went up, the fuzziness increased to an extent were it almost was not linear anymore. | ||
===May 26, 2011=== | |||
This morning was spent troubleshooting a line of code given by Dr. Fitzpatrick, M1<-tapply(MA$M[,1],as.factor(MA$genes[,5]),mean), meant to average the duplicate spots in the .gpr files after they were locally normalized using loess. We had to come back later fix this code using a for loop so that R would normalize all of the .gpr files instead of the one we had specified, 5 given that that was the first column with gene names when we were working on this yesterday. However, this was a .gpr file so the first four columns were just 1's, were as the MA data frame that was created did not incoporate these columns into the data frame. Once this was all figured out, I went to lunch and to check on the S. cerevisiae cultures (see lab notebook for details). Once we got back, we spent the remainder of the time trying to make sure the loess normalization worked, after talking with Dr. Fitzpatrick for a bit we switched our determined this was best done by graphing the normalized vs. nonnormalized log fold changes, after they had both been averaged using the tapply function. We spent a short amount of time trouble shooting this, mostly clerical errors when typing the source code, after which we were able to graph the relationship, which came out to be a relatively linear line, showing that loess normalization was working correctly. With this we are able to go back and do the loess normalization on the data given by the rest of strains. | |||
Revision as of 17:15, 26 May 2011
May 25, 2011
Spent the morning trying to match up the Log Fold Changes before global normalization and after global normalization from the .gpr files. Ideally the graph should have a linear trend line if global normalization had subtracted the same constant from every spot. However, some of the files output a fuzzy region around the origin, this can be seen in the separate powerpoint with the graphs. The individual red/green intensities were graphed next. The normalized red intensities was graphed against the non-normalized red intensities and the same for the green intensities. These graphs should all be a linear line as well, however some awkward points occurred. The fuzzy region from the LogFC graph is thought to be a resultant from the "error" messages that are scattered throughout the .gpr files. These are a result of the intensity ratio being negative and the Log of any negative number does not exist. The number of "error" messages in each file seemed to correlate with the fuzzy section around the origin, as the number of "error"'s went up, the fuzziness increased to an extent were it almost was not linear anymore.
May 26, 2011
This morning was spent troubleshooting a line of code given by Dr. Fitzpatrick, M1<-tapply(MA$M[,1],as.factor(MA$genes[,5]),mean), meant to average the duplicate spots in the .gpr files after they were locally normalized using loess. We had to come back later fix this code using a for loop so that R would normalize all of the .gpr files instead of the one we had specified, 5 given that that was the first column with gene names when we were working on this yesterday. However, this was a .gpr file so the first four columns were just 1's, were as the MA data frame that was created did not incoporate these columns into the data frame. Once this was all figured out, I went to lunch and to check on the S. cerevisiae cultures (see lab notebook for details). Once we got back, we spent the remainder of the time trying to make sure the loess normalization worked, after talking with Dr. Fitzpatrick for a bit we switched our determined this was best done by graphing the normalized vs. nonnormalized log fold changes, after they had both been averaged using the tapply function. We spent a short amount of time trouble shooting this, mostly clerical errors when typing the source code, after which we were able to graph the relationship, which came out to be a relatively linear line, showing that loess normalization was working correctly. With this we are able to go back and do the loess normalization on the data given by the rest of strains.
