HI Bert and Ben, Yes, running lm.fit using the matrix format is much faster. I read a couple of online comments why it is faster. However, the residual values for three tested variables or genes from lm function and lm.fit function are different, with Pearson correlation of 0.55, 0.89, and 0.99. I have not found the reason. Thanks, Ding From: Bert Gunter <bgunter.4567 at gmail.com> Sent: Friday, August 9, 2024 7:11 PM To: Ben Bolker <bbolker at gmail.com> Cc: Yuan Chun Ding <ycding at coh.org>; r-help at r-project.org Subject: Re: [R] a fast way to do my job Better idea, Ben! It would work as you might expect it to to produce the same results as the above: ##first make sure your regressor is a matrix: pur2 <- matrix(purity2, ncol =1) ## convert the data frame variables into a matrix dat <- Better idea, Ben! It would work as you might expect it to to produce the same results as the above: ##first make sure your regressor is a matrix: pur2 <- matrix(purity2, ncol =1) ## convert the data frame variables into a matrix dat <- as.matrix(gem751be.rpkm[ , 74:35164]) ##then result <- residuals(lm.fit( x= pur2, y = dat)) Cheers, Bert On Fri, Aug 9, 2024 at 6:38?PM Ben Bolker <bbolker at gmail.com<mailto:bbolker at gmail.com>> wrote:>> You can also fit a linear model with a matrix-valued response> variable, which should be even faster (not sure off the top of my head> how to get the residuals and reshape them to the dimensions you want)>> On Fri, Aug 9, 2024 at 9:31?PM Bert Gunter <bgunter.4567 at gmail.com<mailto:bgunter.4567 at gmail.com>> wrote:> >> > See ?lm.fit.> > I must be missing something, because:> >> > results <- sapply(74:35164, \(i) residuals(lm.fit(purity2,> > gem751be.rpkm[, i] )))> >> > would give you a 751 x 35091 matrix of the residuals from each of the> > regressions.> > I assume it will be considerably faster than all the overhead you are> > carrying in your current code, but of course you'll have to try it and> > see. ... Assuming that I have interpreted your request correctly.> > Ignore if not.> >> > Cheers,> > Bert> >> > On Fri, Aug 9, 2024 at 4:50?PM Yuan Chun Ding via R-help> > <r-help at r-project.org<mailto:r-help at r-project.org>> wrote:> > >> > > Dear R users,> > >> > > I am running the following code below, the gem751be.rpkm is a dataframe with dim of 751 samples by 35164 variables, 73 phenotypic variables in the furst to 73rd column and 35091 genomic variables or genes in the 74th to 35164th columns. What I need to do is to calculate the residuals for each gene using the simple linear regression model of genelist[i] ~ purity2;> > >> > > The following code is running, it takes long time, but I have an expensive ThinkStation window computer.> > > Can you provide a fast way to do it?> > >> > > Thank you,> > >> > > Ding> > >> > > ---------------------------------------------------------------------------------> > >> > >> > > gem751be.rpkm <-merge(gem751be10, as.data.frame(t(rna849.fpkm2)),> > > + by.x="id2",by.y=0)> > > > row.names(gem751be.rpkm)<-gem751be.rpkm$id3> > > > colnames(gem751be.rpkm)<-gsub(colnames(gem751be.rpkm),pattern="-",replacement="_")> > > > genelist <- gem751be.rpkm %>% dplyr::select(74:35164)> > > > residuals <- NULL> > > > for (i in 1:length(genelist)) {> > > + #i=1> > > + formula <- reformulate("purity2", response=names(genelist)[i])> > > + model <- lm(formula, data = gem751be.rpkm)> > > + resi <- as.data.frame(residuals(model))> > > + colnames(resi)[1]<-names(genelist)[i]> > > + resi <-as.data.frame(t(resi))> > > + residuals <- rbind(residuals, resi)> > > + }> > >> > >> > >> > > ----------------------------------------------------------------------> > > ------------------------------------------------------------> > > -SECURITY/CONFIDENTIALITY WARNING-> > >> > > This message and any attachments are intended solely for the individual or entity to which they are addressed. 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Probably because you inadvertently ran different models. Without your code, I haven't a clue. On Sat, Aug 10, 2024, 12:29 Yuan Chun Ding <ycding at coh.org> wrote:> HI Bert and Ben, > > > > Yes, running lm.fit using the matrix format is much faster. I read a > couple of online comments why it is faster. > > > > However, the residual values for three tested variables or genes from lm > function and lm.fit function are different, with Pearson correlation of > 0.55, 0.89, and 0.99. > > > > I have not found the reason. > > > > Thanks, > > > Ding > > > > *From:* Bert Gunter <bgunter.4567 at gmail.com> > *Sent:* Friday, August 9, 2024 7:11 PM > *To:* Ben Bolker <bbolker at gmail.com> > *Cc:* Yuan Chun Ding <ycding at coh.org>; r-help at r-project.org > *Subject:* Re: [R] a fast way to do my job > > > > Better idea, Ben! It would work as you might expect it to to produce the > same results as the above: ##first make sure your regressor is a matrix: > pur2 <- matrix(purity2, ncol =1) ## convert the data frame variables into a > matrix dat <- > > Better idea, Ben! > > > > It would work as you might expect it to to produce the same results as > > the above: > > > > ##first make sure your regressor is a matrix: > > pur2 <- matrix(purity2, ncol =1) > > ## convert the data frame variables into a matrix > > dat <- as.matrix(gem751be.rpkm[ , 74:35164]) > > ##then > > result <- residuals(lm.fit( x= pur2, y = dat)) > > > > Cheers, > > Bert > > > > On Fri, Aug 9, 2024 at 6:38?PM Ben Bolker <bbolker at gmail.com> wrote: > > > > > > You can also fit a linear model with a matrix-valued response > > > variable, which should be even faster (not sure off the top of my head > > > how to get the residuals and reshape them to the dimensions you want) > > > > > > On Fri, Aug 9, 2024 at 9:31?PM Bert Gunter <bgunter.4567 at gmail.com> wrote: > > > > > > > > See ?lm.fit. > > > > I must be missing something, because: > > > > > > > > results <- sapply(74:35164, \(i) residuals(lm.fit(purity2, > > > > gem751be.rpkm[, i] ))) > > > > > > > > would give you a 751 x 35091 matrix of the residuals from each of the > > > > regressions. > > > > I assume it will be considerably faster than all the overhead you are > > > > carrying in your current code, but of course you'll have to try it and > > > > see. ... Assuming that I have interpreted your request correctly. > > > > Ignore if not. > > > > > > > > Cheers, > > > > Bert > > > > > > > > On Fri, Aug 9, 2024 at 4:50?PM Yuan Chun Ding via R-help > > > > <r-help at r-project.org> wrote: > > > > > > > > > > Dear R users, > > > > > > > > > > I am running the following code below, the gem751be.rpkm is a dataframe with dim of 751 samples by 35164 variables, 73 phenotypic variables in the furst to 73rd column and 35091 genomic variables or genes in the 74th to 35164th columns. What I need to do is to calculate the residuals for each gene using the simple linear regression model of genelist[i] ~ purity2; > > > > > > > > > > The following code is running, it takes long time, but I have an expensive ThinkStation window computer. > > > > > Can you provide a fast way to do it? > > > > > > > > > > Thank you, > > > > > > > > > > Ding > > > > > > > > > > --------------------------------------------------------------------------------- > > > > > > > > > > > > > > > gem751be.rpkm <-merge(gem751be10, as.data.frame(t(rna849.fpkm2)), > > > > > + by.x="id2",by.y=0) > > > > > > row.names(gem751be.rpkm)<-gem751be.rpkm$id3 > > > > > > colnames(gem751be.rpkm)<-gsub(colnames(gem751be.rpkm),pattern="-",replacement="_") > > > > > > genelist <- gem751be.rpkm %>% dplyr::select(74:35164) > > > > > > residuals <- NULL > > > > > > for (i in 1:length(genelist)) { > > > > > + #i=1 > > > > > + formula <- reformulate("purity2", response=names(genelist)[i]) > > > > > + model <- lm(formula, data = gem751be.rpkm) > > > > > + resi <- as.data.frame(residuals(model)) > > > > > + colnames(resi)[1]<-names(genelist)[i] > > > > > + resi <-as.data.frame(t(resi)) > > > > > + residuals <- rbind(residuals, resi) > > > > > + } > > > > > > > > > > > > > > > > > > > > ---------------------------------------------------------------------- > > > > > ------------------------------------------------------------ > > > > > -SECURITY/CONFIDENTIALITY WARNING- > > > > > > > > > > This message and any attachments are intended solely for the individual or entity to which they are addressed. 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Hi Bert and Ben, Thanks a lot for your suggestion!!. About the different residuals between lm function and lm.fit, from online search, lt seems like that I need to add an intercept in the design matrix x; pur2 <- matrix(gem751be.rpkm$purity2, ncol =1) pur2.1 <- cbind(1,gem751be.rpkm$purity2) then running result2 <- residuals(lm.fit( x= pur2.1, y = dat)); now I am thinking whether an intercept is required or not. Ding From: R-help <r-help-bounces at r-project.org> On Behalf Of Yuan Chun Ding via R-help Sent: Saturday, August 10, 2024 12:30 PM To: Bert Gunter <bgunter.4567 at gmail.com>; Ben Bolker <bbolker at gmail.com> Cc: r-help at r-project.org Subject: Re: [R] a fast way to do my job HI Bert and Ben, Yes, running lm.?fit using the matrix format is much faster. I read a couple of online comments why it is faster. However, the residual values for three tested variables or genes from lm function and lm.?fit function are different, HI Bert and Ben, Yes, running lm.fit using the matrix format is much faster. I read a couple of online comments why it is faster. However, the residual values for three tested variables or genes from lm function and lm.fit function are different, with Pearson correlation of 0.55, 0.89, and 0.99. I have not found the reason. Thanks, Ding From: Bert Gunter <bgunter.4567 at gmail.com<mailto:bgunter.4567 at gmail.com>> Sent: Friday, August 9, 2024 7:11 PM To: Ben Bolker <bbolker at gmail.com<mailto:bbolker at gmail.com>> Cc: Yuan Chun Ding <ycding at coh.org<mailto:ycding at coh.org>>; r-help at r-project.org<mailto:r-help at r-project.org> Subject: Re: [R] a fast way to do my job Better idea, Ben! It would work as you might expect it to to produce the same results as the above: ##first make sure your regressor is a matrix: pur2 <- matrix(purity2, ncol =1) ## convert the data frame variables into a matrix dat <- Better idea, Ben! It would work as you might expect it to to produce the same results as the above: ##first make sure your regressor is a matrix: pur2 <- matrix(purity2, ncol =1) ## convert the data frame variables into a matrix dat <- as.matrix(gem751be.rpkm[ , 74:35164]) ##then result <- residuals(lm.fit( x= pur2, y = dat)) Cheers, Bert On Fri, Aug 9, 2024 at 6:38?PM Ben Bolker <bbolker at gmail.com<mailto:bbolker at gmail.com<mailto:bbolker at gmail.com%3cmailto:bbolker at gmail.com>>> wrote:>> You can also fit a linear model with a matrix-valued response> variable, which should be even faster (not sure off the top of my head> how to get the residuals and reshape them to the dimensions you want)>> On Fri, Aug 9, 2024 at 9:31?PM Bert Gunter <bgunter.4567 at gmail.com<mailto:bgunter.4567 at gmail.com<mailto:bgunter.4567 at gmail.com%3cmailto:bgunter.4567 at gmail.com>>> wrote:> >> > See ?lm.fit.> > I must be missing something, because:> >> > results <- sapply(74:35164, \(i) residuals(lm.fit(purity2,> > gem751be.rpkm[, i] )))> >> > would give you a 751 x 35091 matrix of the residuals from each of the> > regressions.> > I assume it will be considerably faster than all the overhead you are> > carrying in your current code, but of course you'll have to try it and> > see. ... Assuming that I have interpreted your request correctly.> > Ignore if not.> >> > Cheers,> > Bert> >> > On Fri, Aug 9, 2024 at 4:50?PM Yuan Chun Ding via R-help> > <r-help at r-project.org<mailto:r-help at r-project.org<mailto:r-help at r-project.org%3cmailto:r-help at r-project.org>>> wrote:> > >> > > Dear R users,> > >> > > I am running the following code below, the gem751be.rpkm is a dataframe with dim of 751 samples by 35164 variables, 73 phenotypic variables in the furst to 73rd column and 35091 genomic variables or genes in the 74th to 35164th columns. What I need to do is to calculate the residuals for each gene using the simple linear regression model of genelist[i] ~ purity2;> > >> > > The following code is running, it takes long time, but I have an expensive ThinkStation window computer.> > > Can you provide a fast way to do it?> > >> > > Thank you,> > >> > > Ding> > >> > > ---------------------------------------------------------------------------------> > >> > >> > > gem751be.rpkm <-merge(gem751be10, as.data.frame(t(rna849.fpkm2)),> > > + by.x="id2",by.y=0)> > > > row.names(gem751be.rpkm)<-gem751be.rpkm$id3> > > > colnames(gem751be.rpkm)<-gsub(colnames(gem751be.rpkm),pattern="-",replacement="_")> > > > genelist <- gem751be.rpkm %>% dplyr::select(74:35164)> > > > residuals <- NULL> > > > for (i in 1:length(genelist)) {> > > + #i=1> > > + formula <- reformulate("purity2", response=names(genelist)[i])> > > + model <- lm(formula, data = gem751be.rpkm)> > > + resi <- as.data.frame(residuals(model))> > > + colnames(resi)[1]<-names(genelist)[i]> > > + resi <-as.data.frame(t(resi))> > > + residuals <- rbind(residuals, resi)> > > + }> > >> > >> > >> > > ----------------------------------------------------------------------> > > ------------------------------------------------------------> > > -SECURITY/CONFIDENTIALITY WARNING-> > >> > > This message and any attachments are intended solely for the individual or entity to which they are addressed. 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> PLEASE do read the posting guide https://urldefense.com/v3/__http://www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX66rfmKvA$<https://urldefense.com/v3/__http:/www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX66rfmKvA$><https://urldefense.com/v3/__http:/www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX66rfmKvA$%3chttps:/urldefense.com/v3/__http:/www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX66rfmKvA$%3e%3e><https://urldefense.com/v3/__http:/www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX66rfmKvA$%3chttps:/urldefense.com/v3/__http:/www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX66rfmKvA$%3e%3e>><https://urldefense.com/v3/__http:/www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX66rfmKvA$%3chttps:/urldefense.com/v3/__http:/www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX66rfmKvA$%3e%3e>> > and provide commented, minimal, self-contained, reproducible code.> >> > ______________________________________________> > R-help at r-project.org<mailto:R-help at r-project.org<mailto:R-help at r-project.org%3cmailto:R-help at r-project.org>> mailing list -- To UNSUBSCRIBE and more, see> > https://urldefense.com/v3/__https://stat.ethz.ch/mailman/listinfo/r-help__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX72PW30DQ$<https://urldefense.com/v3/__https:/stat.ethz.ch/mailman/listinfo/r-help__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX72PW30DQ$><https://urldefense.com/v3/__https:/stat.ethz.ch/mailman/listinfo/r-help__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX72PW30DQ$%3chttps:/urldefense.com/v3/__https:/stat.ethz.ch/mailman/listinfo/r-help__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX72PW30DQ$%3e%3e><https://urldefense.com/v3/__https:/stat.ethz.ch/mailman/listinfo/r-help__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX72PW30DQ$%3chttps:/urldefense.com/v3/__https:/stat.ethz.ch/mailman/listinfo/r-help__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX72PW30DQ$%3e%3e>><https://urldefense.com/v3/__https:/stat.ethz.ch/mailman/listinfo/r-help__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX72PW30DQ$%3chttps:/urldefense.com/v3/__https:/stat.ethz.ch/mailman/listinfo/r-help__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX72PW30DQ$%3e%3e>> PLEASE do read the posting guide https://urldefense.com/v3/__http://www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX66rfmKvA$<https://urldefense.com/v3/__http:/www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX66rfmKvA$><https://urldefense.com/v3/__http:/www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX66rfmKvA$%3chttps:/urldefense.com/v3/__http:/www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX66rfmKvA$%3e%3e><https://urldefense.com/v3/__http:/www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX66rfmKvA$%3chttps:/urldefense.com/v3/__http:/www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX66rfmKvA$%3e%3e>><https://urldefense.com/v3/__http:/www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX66rfmKvA$%3chttps:/urldefense.com/v3/__http:/www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qcJ4z-vlMNzsa8XCsJUcuPOz8Vt12zsV_XaWpqXsyUYJBTlcNRonFPr7w7Ql3xqcDnZ9ZYC8JX66rfmKvA$%3e%3e>> and provide commented, minimal, self-contained, reproducible code.[[alternative HTML version deleted]] ______________________________________________ R-help at r-project.org<mailto:R-help at r-project.org> mailing list -- To UNSUBSCRIBE and more, see https://urldefense.com/v3/__https://stat.ethz.ch/mailman/listinfo/r-help__;!!Fou38LsQmgU!qqGp8uiTt4Nzt-4q2_z-dVpb3v8sQFbRq5O7Nok73NE3PTvgaktKByzXHf3KUh9X0Z4OaDMB0o_GD0c$<https://urldefense.com/v3/__https:/stat.ethz.ch/mailman/listinfo/r-help__;!!Fou38LsQmgU!qqGp8uiTt4Nzt-4q2_z-dVpb3v8sQFbRq5O7Nok73NE3PTvgaktKByzXHf3KUh9X0Z4OaDMB0o_GD0c$> PLEASE do read the posting guide https://urldefense.com/v3/__http://www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qqGp8uiTt4Nzt-4q2_z-dVpb3v8sQFbRq5O7Nok73NE3PTvgaktKByzXHf3KUh9X0Z4OaDMBoUteypM$<https://urldefense.com/v3/__http:/www.R-project.org/posting-guide.html__;!!Fou38LsQmgU!qqGp8uiTt4Nzt-4q2_z-dVpb3v8sQFbRq5O7Nok73NE3PTvgaktKByzXHf3KUh9X0Z4OaDMBoUteypM$> and provide commented, minimal, self-contained, reproducible code. 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