Question: Query related to topGene functionality in RankProd library.
0
gravatar for Fangxin Hong
9.9 years ago by
Fangxin Hong20
Fangxin Hong20 wrote:
Hi Rohan, Please see my comments below, > >> -----Original Message----- >> From: bioconductor-bounces at stat.math.ethz.ch [mailto:bioconductor- >> bounces at stat.math.ethz.ch] On Behalf Of Rohan M >> Sent: Monday, December 07, 2009 6:55 AM >> To: bioconductor at stat.math.ethz.ch >> Subject: [BioC] Query related to topGene functionality in RankProd >> library. >> >> Dear Sir, >> >> I'm using RankProd library to find the significant genes in microarray >> studies. I'm facing some problems in understanding the output of >> topGene >> functionality. >> Could you help me on following queries? >> >> 1) The topGene functionality outputs >> Table1: Genes called significant under class1 < class2 (Up regulated >> Genes) >> and Table2: Genes called significant under class1 > class2 (Down >> regulated >> genes). When I see the fold change value in both tables , there are >> some >> genes having fold change value less than 1 in Table 1 and some genes >> have >> fold change value greater than 1 in Table 2. >> "If the Gene has fold change value less than 1 then its down regulated" >> how >> can I interpret fold change value (up regulated or down regulated ) in >> such >> case? >> Theoretically this shouldn't happen as expression level is suppressed when downregulated. I don't know what cutoff point you selected for topGene. If you use a loose criteria, which would lead to gene with not strong signal being identified out, this would happen. For example, if gene A has 4 fold-change readout (in one-channel case) as 1.6,0.9,0.7,0.9 then the average fold-change is1.025. However, this gene might be identified in downregulation list as 3 out of 4 fold changes are less than 1. 2) In some cases both Table 1 and Table 2 contains same probe. Is it >> possible to have one probe present in both tables? If Yes, then which >> one >> should be considered? >> This type result would very much indicate this gene doesn't have decent signal in either direction. This would happen when random variation gives fake signal in both direction, when For example, a gene with 4 fold-changes of 1.3, 0.6, 0.9, 1.2 would results in both list if a loose cut-off point is selected. >> 3) Sometime I see "Inf" as fold change value - must be infinity. Is it >> possible to have such value? >> If there is 0 or negative value in the expression data (like the one normalized with MAS5), then it is possible. As stated in package manual, it is always a good to look at the data when such results coming out, which would help a lot in term of selecting cut-off point and interpret results Hope this would help, let me know if this is not clear or you prefer to send over your data for mt to take a look. Best, Fangxin >> Could you please help me understanding the above points? >> >> Thanks and regards, >> Rohan >> >> [[alternative HTML version deleted]] >> >> _______________________________________________ >> Bioconductor mailing list >> Bioconductor at stat.math.ethz.ch >> https://stat.ethz.ch/mailman/listinfo/bioconductor >> Search the archives: >> http://news.gmane.org/gmane.science.biology.informatics.conductor >> -- Fangxin Hong Ph.D. Research Scientist Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute, Harvard School of Public Health Phone: 617-632-3602 Email: fxhong at jimmy.harvard.edu
cancer probe rankprod • 767 views
ADD COMMENTlink modified 9.9 years ago by Rohan M20 • written 9.9 years ago by Fangxin Hong20
Answer: Query related to topGene functionality in RankProd library.
0
gravatar for Rohan M
9.9 years ago by
Rohan M20
Rohan M20 wrote:
Dear Fangxin, Thank you very much for looking into mail and replying promptly, I really appreciate it. For answers to question 2 and 3, I understood the points. I cross checked that the data was normalized using MAS algorithm. Regarding question 1 here are few more details - I'm using two class data with Single origin to calculate Rank product. For example, Class A contains 20 samples and Class B contains 10 samples. I'm using following cutoff for the topGene functionality. *classes - The vector to assign two classes labels.* *RP.out <- RP(arab, classes, num.perm = 100, logged = TRUE,na.rm = FALSE, plot = FALSE, rand = 123) outPut <- topGene(RP.out, cutoff = 0.05, method = "pfp", logged = TRUE, logbase = 2, gene.names = rownames(arab))* Is the cutoff 0.05 enough or need to be more stringent? Also, with this set up is it possible to have FC value more than 1 in Table1 or FC value less than 1 in Table2 for many probes? Thank you once again. Regards, Rohan On Tue, Dec 8, 2009 at 12:16 AM, Fangxin Hong <fxhong@jimmy.harvard.edu>wrote: > Hi Rohan, > Please see my comments below, > > > >> >>> -----Original Message----- >>> From: bioconductor-bounces@stat.math.ethz.ch [mailto:bioconductor- >>> bounces@stat.math.ethz.ch] On Behalf Of Rohan M >>> Sent: Monday, December 07, 2009 6:55 AM >>> To: bioconductor@stat.math.ethz.ch >>> Subject: [BioC] Query related to topGene functionality in RankProd >>> library. >>> >>> Dear Sir, >>> >>> I'm using RankProd library to find the significant genes in microarray >>> studies. I'm facing some problems in understanding the output of >>> topGene >>> functionality. >>> Could you help me on following queries? >>> >>> 1) The topGene functionality outputs >>> Table1: Genes called significant under class1 < class2 (Up regulated >>> Genes) >>> and Table2: Genes called significant under class1 > class2 (Down >>> regulated >>> genes). When I see the fold change value in both tables , there are >>> some >>> genes having fold change value less than 1 in Table 1 and some genes >>> have >>> fold change value greater than 1 in Table 2. >>> "If the Gene has fold change value less than 1 then its down regulated" >>> how >>> can I interpret fold change value (up regulated or down regulated ) in >>> such >>> case? >>> >>> >> Theoretically this shouldn't happen as expression level is suppressed when > downregulated. I don't know what cutoff point you selected for topGene. > If you use a loose criteria, which would lead to gene with not strong > signal being identified out, this would happen. > For example, if gene A has 4 fold-change readout (in one-channel case) as > 1.6,0.9,0.7,0.9 then the average fold-change is1.025. However, this gene > might be identified in downregulation list as 3 out of 4 fold changes are > less than 1. > > > 2) In some cases both Table 1 and Table 2 contains same probe. Is it > >> possible to have one probe present in both tables? If Yes, then which >>> one >>> should be considered? >>> >>> >> This type result would very much indicate this gene doesn't have decent > signal in either direction. This would happen when random variation gives > fake signal in both direction, when > For example, a gene with 4 fold-changes of 1.3, 0.6, 0.9, 1.2 would > results in both list if a loose cut-off point is selected. > > 3) Sometime I see "Inf" as fold change value - must be infinity. Is it >>> possible to have such value? >>> >>> >> If there is 0 or negative value in the expression data (like the one > normalized with MAS5), then it is possible. > > > As stated in package manual, it is always a good to look at the data when > such results coming out, which would help a lot in term of selecting cut-off > point and interpret results > > Hope this would help, let me know if this is not clear or you prefer to > send over your data for mt to take a look. > > Best, > Fangxin > > Could you please help me understanding the above points? >>> >>> Thanks and regards, >>> Rohan >>> >>> [[alternative HTML version deleted]] >>> >>> _______________________________________________ >>> Bioconductor mailing list >>> Bioconductor@stat.math.ethz.ch >>> https://stat.ethz.ch/mailman/listinfo/bioconductor >>> Search the archives: >>> http://news.gmane.org/gmane.science.biology.informatics.conductor >>> >>> >> > -- > > Fangxin Hong Ph.D. > Research Scientist > Department of Biostatistics and Computational Biology > Dana-Farber Cancer Institute, Harvard School of Public Health > Phone: 617-632-3602 > Email: fxhong@jimmy.harvard.edu > > [[alternative HTML version deleted]]
ADD COMMENTlink written 9.9 years ago by Rohan M20
Hi Rohan, What I suspect is some "outliers" or extreme values that screw up the average fold-change, especially when you have uneven design (different # of samples in two group), for example for given gene , its readout under class A (4 samples) are: 100,300,60,80, and under class B ( 2 samples) are: 120, 140 => average fold-change (sample1/sample2)=1.038 However, it is likely that 300 value is an outlier since it is not consistent with other three meaurement, therefore this gene is likely downregulated in class A compared with class B though the average FC >1. In fact this is the power of rankproduct method as it is much more robust against outlier than t-like statistics which will call this gene up-regulated in class A. If you prefer, you would send me the expression of such genes over these 20 samples so that I would take a look ? Best, Fangxin Rohan M wrote: > Dear Fangxin, > > Thank you very much for looking into mail and replying promptly, I > really appreciate it. > For answers to question 2 and 3, I understood the points. I cross > checked that the data was normalized using MAS algorithm. > > Regarding question 1 here are few more details - > I'm using two class data with Single origin to calculate Rank product. > For example, Class A contains 20 samples and Class B contains 10 > samples. I'm using following cutoff for the topGene functionality. > > /classes - The vector to assign two classes labels./ > /RP.out <- RP(arab, classes, num.perm = 100, logged = TRUE,na.rm = > FALSE, plot = FALSE, rand = 123) > outPut <- topGene(RP.out, cutoff = 0.05, method = "pfp", logged = > TRUE, logbase = 2, gene.names = rownames(arab))/ > > Is the cutoff 0.05 enough or need to be more stringent? Also, with > this set up is it possible to have FC value more than 1 in Table1 or > FC value less than 1 in Table2 for many probes? > > Thank you once again. > > Regards, > Rohan > > On Tue, Dec 8, 2009 at 12:16 AM, Fangxin Hong > <fxhong at="" jimmy.harvard.edu="" <mailto:fxhong="" at="" jimmy.harvard.edu="">> wrote: > > Hi Rohan, > Please see my comments below, > > > > > -----Original Message----- > From: bioconductor-bounces at stat.math.ethz.ch > <mailto:bioconductor-bounces at="" stat.math.ethz.ch=""> > [mailto:bioconductor- <mailto:bioconductor-> > bounces at stat.math.ethz.ch > <mailto:bounces at="" stat.math.ethz.ch="">] On Behalf Of Rohan M > Sent: Monday, December 07, 2009 6:55 AM > To: bioconductor at stat.math.ethz.ch > <mailto:bioconductor at="" stat.math.ethz.ch=""> > Subject: [BioC] Query related to topGene functionality in > RankProd > library. > > Dear Sir, > > I'm using RankProd library to find the significant genes > in microarray > studies. I'm facing some problems in understanding the > output of > topGene > functionality. > Could you help me on following queries? > > 1) The topGene functionality outputs > Table1: Genes called significant under class1 < class2 (Up > regulated > Genes) > and Table2: Genes called significant under class1 > class2 > (Down > regulated > genes). When I see the fold change value in both tables , > there are > some > genes having fold change value less than 1 in Table 1 and > some genes > have > fold change value greater than 1 in Table 2. > "If the Gene has fold change value less than 1 then its > down regulated" > how > can I interpret fold change value (up regulated or down > regulated ) in > such > case? > > > Theoretically this shouldn't happen as expression level is > suppressed when downregulated. I don't know what cutoff point you > selected for topGene. > If you use a loose criteria, which would lead to gene with not > strong signal being identified out, this would happen. > For example, if gene A has 4 fold-change readout (in one- channel > case) as 1.6,0.9,0.7,0.9 then the average fold-change is1.025. > However, this gene might be identified in downregulation list as 3 > out of 4 fold changes are less than 1. > > > 2) In some cases both Table 1 and Table 2 contains same probe. Is it > > possible to have one probe present in both tables? If Yes, > then which > one > should be considered? > > > This type result would very much indicate this gene doesn't have > decent signal in either direction. This would happen when random > variation gives fake signal in both direction, when > For example, a gene with 4 fold-changes of 1.3, 0.6, 0.9, 1.2 > would results in both list if a loose cut-off point is selected. > > 3) Sometime I see "Inf" as fold change value - must be > infinity. Is it > possible to have such value? > > > If there is 0 or negative value in the expression data (like the > one normalized with MAS5), then it is possible. > > > As stated in package manual, it is always a good to look at the > data when such results coming out, which would help a lot in term > of selecting cut-off point and interpret results > > Hope this would help, let me know if this is not clear or you > prefer to send over your data for mt to take a look. > > Best, > Fangxin > > Could you please help me understanding the above points? > > Thanks and regards, > Rohan > > [[alternative HTML version deleted]] > > _______________________________________________ > Bioconductor mailing list > Bioconductor at stat.math.ethz.ch > <mailto:bioconductor at="" stat.math.ethz.ch=""> > https://stat.ethz.ch/mailman/listinfo/bioconductor > Search the archives: > http://news.gmane.org/gmane.science.biology.informatics.conductor > > > > -- > > Fangxin Hong Ph.D. > Research Scientist > Department of Biostatistics and Computational Biology > Dana-Farber Cancer Institute, Harvard School of Public Health > Phone: 617-632-3602 > Email: fxhong at jimmy.harvard.edu <mailto:fxhong at="" jimmy.harvard.edu=""> > > -- Fangxin Hong Ph.D. Research Scientist Department of Biostatistics and Computational Biology Dana-Farber Cancer Institute, Harvard School of Public Health Phone: 617-632-3602 Email: fxhong at jimmy.harvard.edu
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