runSPIA() in graphite package
2
0
Entering edit mode
array chip ▴ 420
@array-chip-4136
Last seen 9 months ago
United States
Hi all, I am using runSPIA() from graphite package to analyze a gene list against biocarta pathway database. > library(graphite) > prepareSPIA(biocarta, "biocartaEx") > obj<-runSPIA(de=siggenes, all=allgenes, "biocartaEx") where "siggenes" are a list of 1332 significant genes selected from "allgenes" (a list of 17138 genes). The running process verbose indicated a total of 178 pathways analyzed. One of the pathways I am particularly interested is "estrogen responsive protein efp controls cell cycle and breast tumors growth": > p <- biocarta[["estrogen responsive protein efp controls cell cycle and breast tumors growth"]] > nodes(p) [1] "CDKs"???????????? "Cyclin B1/2"????? "EntrezGene:2099"? "EntrezGene:2810"? "EntrezGene:57154" "EntrezGene:7157"? "EntrezGene:7706"?? "ubiquitin" And my siggenes contains 2 of genes involved in this pathway: > siggenes[c('7706','2099')] ???? 7706????? 2099 ?4.347012 -3.792425 So I would assume that runSPIA will examine this pathway during the? calculation, but surprisingly I didn't see this particular way being examined. Here is the section of runSPIA() verbose output that started with "e": Done pathway 42 : e2f1 destruction pathway.. Done pathway 43 : effects of calcineurin in kera.. Done pathway 44 : egf signaling pathway.. Done pathway 45 : endocytotic role of ndk phosph.. Done pathway 46 : epo signaling pathway.. Done pathway 47 : erk and pi-3 kinase are necess.. Done pathway 48 : erk1/erk2 mapk signaling pathw.. Done pathway 49 : eukaryotic protein translation.. Done pathway 50 : extrinsic prothrombin activati.. Can anyone tell me why runSPIA() missed this pathway? Attached are siggenes and allgenes for you to try.? > siggenes<-as.matrix(read.table("siggenes.txt",row.names=1))[,1] > allgenes<-as.matrix(read.table("H:\\test\\allgenes.txt", row.names=NULL, header=T, colClasses='character'))[,1] Many thanks John -------------- next part -------------- An embedded and charset-unspecified text was scrubbed... Name: allgenes.txt URL: <https: stat.ethz.ch="" pipermail="" bioconductor="" attachments="" 20130208="" 1a59d276="" attachment.txt=""> -------------- next part -------------- An embedded and charset-unspecified text was scrubbed... Name: siggenes.txt URL: <https: stat.ethz.ch="" pipermail="" bioconductor="" attachments="" 20130208="" 1a59d276="" attachment-0001.txt="">
Pathways Breast siggenes PROcess cycle graphite Pathways Breast siggenes PROcess cycle • 2.2k views
ADD COMMENT
0
Entering edit mode
array chip ▴ 420
@array-chip-4136
Last seen 9 months ago
United States
Dear Enrica, Thanks very much for checking this out! graphite is a great package for pathway analysis with its ability to analyze so many different pathway databases! One more question, does runSPIA() run against these pathways on the fly (i.e. access these databases from their server in real time), or against a pre-downloaded database? Do you have a timeline when the new release graphite package will become available? Thanks again for your great work. John ________________________________ From: Enrica <enrica.calura@gmail.com> Cc: Bioconductor mailing list <bioconductor@stat.math.ethz.ch>; "gabriele.sales@unipd.it" <gabriele.sales@unipd.it>; "chiara.romualdi@unipd.it" <chiara.romualdi@unipd.it> Sent: Monday, February 11, 2013 3:24 AM Subject: Re: runSPIA() in graphite package Dear John, the procedure you applied to analyse your data is right. However, the runSpia function filters out those pathways that have no edges or less than 5 nodes with valid edges. Your pathway, after the conversion to Entrez Gene, do not satisfy neither the conditions, having no edges. > pe<-convertIdentifiers(biocarta[["estrogen responsive protein efp controls cell cycle and breast tumors growth"]], "entrez") > pe "estrogen responsive protein efp controls cell cycle and breast tumors growth" pathway from BioCarta Number of nodes     = 5 Number of edges     = 0 Type of identifiers = Entrez Gene Retrieved on        = 2011-05-12 We equipped our runSpia() function with the checks described above in order to protect the user from unreliable results. On a separate note, we have also re-checked how that specific pathway was converted. The original BioPax2 contained some edges, but their endpoints were unfortunately nodes which could not be associated with any entrez gene. Our software, thus, dropped them from the pathway. We are working on a new graphite release based on annotation released more recently. Those includes more edges; as a result that pathway is no longer empty. Enrica Calura Hi all, I am using runSPIA() from graphite package to analyze a gene list against biocarta pathway database. > > > >> library(graphite) > >> prepareSPIA(biocarta, "biocartaEx") >> obj<-runSPIA(de=siggenes, all=allgenes, "biocartaEx") > > > >where "siggenes" are a list of 1332 significant genes selected from "allgenes" (a list of 17138 genes). The running process verbose indicated a total of 178 pathways analyzed. > > > >One of the pathways I am particularly interested is "estrogen responsive protein efp controls cell cycle and breast tumors growth": > > >> p <- biocarta[["estrogen responsive protein efp controls cell cycle and breast tumors growth"]] >> nodes(p) >[1] "CDKs"             "Cyclin B1/2"      "EntrezGene:2099" "EntrezGene:2810"  "EntrezGene:57154" "EntrezGene:7157" "EntrezGene:7706"   "ubiquitin" > > >And my siggenes contains 2 of genes involved in this pathway: > > >> siggenes[c('7706','2099')] >     7706      2099 > 4.347012 -3.792425 > > >So I would assume that runSPIA will examine this pathway during the calculation, but surprisingly I didn't see this particular way being examined. Here is the section of runSPIA() verbose output that started with "e": > > >Done pathway 42 : e2f1 destruction pathway.. >Done pathway 43 : effects of calcineurin in kera.. >Done pathway 44 : egf signaling pathway.. >Done pathway 45 : endocytotic role of ndk phosph.. >Done pathway 46 : epo signaling pathway.. >Done pathway 47 : erk and pi-3 kinase are necess.. >Done pathway 48 : erk1/erk2 mapk signaling pathw.. >Done pathway 49 : eukaryotic protein translation.. >Done pathway 50 : extrinsic prothrombin activati.. > > > >Can anyone tell me why runSPIA() missed this pathway? Attached are siggenes and allgenes for you to try. > > >> siggenes<-as.matrix(read.table("siggenes.txt",row.names=1))[,1] > >> allgenes<-as.matrix(read.table("H:\\test\\allgenes.txt", row.names=NULL, header=T, colClasses='character'))[,1] > > >Many thanks > > >John > > [[alternative HTML version deleted]]
ADD COMMENT
0
Entering edit mode
Thanks John for your appreciation and feedback! Unfortunately is not possible analyse pathways on the fly. The conversion procedure that transforms pathways into networks is intensive, therefore we perform the conversion outside the R environment and than we insert the networks within our R package. We are currently working on the graphite update, we hope to be ready before the next Bioconductor release. Enrica Calura ******************************* Enrica Calura, Ph.D. student, c/o Lab Romualdi via U. Bassi 58/b 35121 Padova, Italy Tel: 049 8276319 e-mail: enrica.calura@gmail.com http://romualdi.bio.unipd.it/ array chip <arrayprofile@yahoo.com> > Dear Enrica, > > Thanks very much for checking this out! graphite is a great package for > pathway analysis with its ability to analyze so many different pathway > databases! > > One more question, does runSPIA() run against these pathways on the fly > (i.e. access these databases from their server in real time), or against a > pre-downloaded database? > > Do you have a timeline when the new release graphite package will become > available? > > Thanks again for your great work. > > John > > > ------------------------------ > *From:* Enrica <enrica.calura@gmail.com> > *To:* array chip <arrayprofile@yahoo.com> > *Cc:* Bioconductor mailing list <bioconductor@stat.math.ethz.ch>; " > gabriele.sales@unipd.it" <gabriele.sales@unipd.it>; " > chiara.romualdi@unipd.it" <chiara.romualdi@unipd.it> > *Sent:* Monday, February 11, 2013 3:24 AM > *Subject:* Re: runSPIA() in graphite package > > Dear John, > > the procedure you applied to analyse your data is right. > However, the runSpia function filters out those pathways that have no > edges or less than 5 nodes with valid edges. Your pathway, after the > conversion to Entrez Gene, do not satisfy neither the conditions, having no > edges. > > > pe<-convertIdentifiers(biocarta[["estrogen responsive protein efp > controls cell cycle and breast tumors growth"]], "entrez") > > pe > "estrogen responsive protein efp controls cell cycle and breast tumors > growth" pathway from BioCarta > Number of nodes = 5 > Number of edges = 0 > Type of identifiers = Entrez Gene > Retrieved on = 2011-05-12 > > We equipped our runSpia() function with the checks described above in > order to protect the user from unreliable results. > > On a separate note, we have also re-checked how that specific pathway was > converted. The original BioPax2 contained some edges, but their endpoints > were unfortunately nodes which could not be associated with any entrez > gene. Our software, thus, dropped them from the pathway. > We are working on a new graphite release based on annotation released more > recently. Those includes more edges; as a result that pathway is no longer > empty. > > Enrica Calura > > > > > > > 2013/2/8 array chip <arrayprofile@yahoo.com> > > Hi all, I am using runSPIA() from graphite package to analyze a gene list > against biocarta pathway database. > > > library(graphite) > > prepareSPIA(biocarta, "biocartaEx") > > obj<-runSPIA(de=siggenes, all=allgenes, "biocartaEx") > > where "siggenes" are a list of 1332 significant genes selected from > "allgenes" (a list of 17138 genes). The running process verbose indicated a > total of 178 pathways analyzed. > > One of the pathways I am particularly interested is "estrogen responsive > protein efp controls cell cycle and breast tumors growth": > > > p <- biocarta[["estrogen responsive protein efp controls cell cycle and > breast tumors growth"]] > > nodes(p) > [1] "CDKs" "Cyclin B1/2" "EntrezGene:2099" > "EntrezGene:2810" "EntrezGene:57154" "EntrezGene:7157" > "EntrezGene:7706" "ubiquitin" > > And my siggenes contains 2 of genes involved in this pathway: > > > siggenes[c('7706','2099')] > 7706 2099 > 4.347012 -3.792425 > > So I would assume that runSPIA will examine this pathway during the > calculation, but surprisingly I didn't see this particular way being > examined. Here is the section of runSPIA() verbose output that started with > "e": > > Done pathway 42 : e2f1 destruction pathway.. > Done pathway 43 : effects of calcineurin in kera.. > Done pathway 44 : egf signaling pathway.. > Done pathway 45 : endocytotic role of ndk phosph.. > Done pathway 46 : epo signaling pathway.. > Done pathway 47 : erk and pi-3 kinase are necess.. > Done pathway 48 : erk1/erk2 mapk signaling pathw.. > Done pathway 49 : eukaryotic protein translation.. > Done pathway 50 : extrinsic prothrombin activati.. > > Can anyone tell me why runSPIA() missed this pathway? Attached are > siggenes and allgenes for you to try. > > > siggenes<-as.matrix(read.table("siggenes.txt",row.names=1))[,1] > > allgenes<-as.matrix(read.table("H:\\test\\allgenes.txt", row.names=NULL, > header=T, colClasses='character'))[,1] > > Many thanks > > John > > > > > -- ********************************** [[alternative HTML version deleted]]
ADD REPLY
0
Entering edit mode
Enrica ▴ 20
@enrica-5756
Last seen 10.2 years ago
Dear John, the procedure you applied to analyse your data is right. However, the runSpia function filters out those pathways that have no edges or less than 5 nodes with valid edges. Your pathway, after the conversion to Entrez Gene, do not satisfy neither the conditions, having no edges. > pe<-convertIdentifiers(biocarta[["estrogen responsive protein efp controls cell cycle and breast tumors growth"]], "entrez") > pe "estrogen responsive protein efp controls cell cycle and breast tumors growth" pathway from BioCarta Number of nodes = 5 Number of edges = 0 Type of identifiers = Entrez Gene Retrieved on = 2011-05-12 We equipped our runSpia() function with the checks described above in order to protect the user from unreliable results. On a separate note, we have also re-checked how that specific pathway was converted. The original BioPax2 contained some edges, but their endpoints were unfortunately nodes which could not be associated with any entrez gene. Our software, thus, dropped them from the pathway. We are working on a new graphite release based on annotation released more recently. Those includes more edges; as a result that pathway is no longer empty. Enrica Calura 2013/2/8 array chip <arrayprofile@yahoo.com> > Hi all, I am using runSPIA() from graphite package to analyze a gene list > against biocarta pathway database. > > > library(graphite) > > prepareSPIA(biocarta, "biocartaEx") > > obj<-runSPIA(de=siggenes, all=allgenes, "biocartaEx") > > where "siggenes" are a list of 1332 significant genes selected from > "allgenes" (a list of 17138 genes). The running process verbose indicated a > total of 178 pathways analyzed. > > One of the pathways I am particularly interested is "estrogen responsive > protein efp controls cell cycle and breast tumors growth": > > > p <- biocarta[["estrogen responsive protein efp controls cell cycle and > breast tumors growth"]] > > nodes(p) > [1] "CDKs" "Cyclin B1/2" "EntrezGene:2099" > "EntrezGene:2810" "EntrezGene:57154" "EntrezGene:7157" > "EntrezGene:7706" "ubiquitin" > > And my siggenes contains 2 of genes involved in this pathway: > > > siggenes[c('7706','2099')] > 7706 2099 > 4.347012 -3.792425 > > So I would assume that runSPIA will examine this pathway during the > calculation, but surprisingly I didn't see this particular way being > examined. Here is the section of runSPIA() verbose output that started with > "e": > > Done pathway 42 : e2f1 destruction pathway.. > Done pathway 43 : effects of calcineurin in kera.. > Done pathway 44 : egf signaling pathway.. > Done pathway 45 : endocytotic role of ndk phosph.. > Done pathway 46 : epo signaling pathway.. > Done pathway 47 : erk and pi-3 kinase are necess.. > Done pathway 48 : erk1/erk2 mapk signaling pathw.. > Done pathway 49 : eukaryotic protein translation.. > Done pathway 50 : extrinsic prothrombin activati.. > > Can anyone tell me why runSPIA() missed this pathway? Attached are > siggenes and allgenes for you to try. > > > siggenes<-as.matrix(read.table("siggenes.txt",row.names=1))[,1] > > allgenes<-as.matrix(read.table("H:\\test\\allgenes.txt", row.names=NULL, > header=T, colClasses='character'))[,1] > > Many thanks > > John > > [[alternative HTML version deleted]]
ADD COMMENT

Login before adding your answer.

Traffic: 680 users visited in the last hour
Help About
FAQ
Access RSS
API
Stats

Use of this site constitutes acceptance of our User Agreement and Privacy Policy.

Powered by the version 2.3.6