Dear Group when I run background(using GCRMA) correction for chips: "10_1331.1I.R208L.CEL" "9_C101.1F.R9F2L.CEL" and for chips "10_1195.1E.R119U.CEL" "9_C101.1F.R9F2L.CEL" keeping 9_C101.1F.R9F2L.CEL as constant, For both the runs I get slightly different outputs for chip 9_C101.1F.R9F2L.CEL (Data below). This does not happen when GSB.adjust is set to FALSE. Also we have noticed the variation seem to get lesser when we try more chips together.Any reason why it should be happening this way? Many thanks Sucheta My code: ------- obj<-ReadAffy(filenames=file) tmp1<-bg.adjust.gcrma(obj,optical.correct=T,affinity.info=affinfo) outfile<-paste(outdir, celfile[i,1], "_bg.txt", sep="") write.table(pm(tmp1), file=outfile, row.names=FALSE, col.names=TRUE, sep="\t") ---------------------------------------------------------------------- "10_1331.1I.R208L.CEL" "9_C101.1F.R9F2L.CEL" --------------------------------------------- 12.5854077145271 4.27009199115734 135.577788495271 115.177321956904 113.171763014501 124.781182045557 2.69508615100678 13.3527712251500 14.5462397159524 36.7662738574386 94.6480456343775 48.972931999473 230.750229599019 212.534925776574 242.058765502072 337.251490520153 233.871977591185 339.413283090951 134.355125363486 108.047618775561 136.685235380017 126.239703801863 76.2625488684543 45.3623158856175 148.251139760089 120.315265011794 328.121529159736 319.366509787047 291.865380794849 361.992073209429 3.97218796139000 4.20902848830535 14.6419514021341 31.6450267847893 28.8699339528603 67.3237575282198 110.496037483661 111.806067290232 22.2876523362755 41.5481196151883 205.194483921088 276.995029856902 84.8559677803056 96.0077121491932 778.222646971625 559.863168099135 4.83202857118797 11.3149613102092 3.66166154528273 39.6717762417948 67.7761672656053 94.6394189279102 112.500673213605 190.985739398352 171.007645212454 200.035151512867 492.236603432973 352.584270678829 130.800353580651 155.324195356517 146.303381286542 160.442554666605 4.34069757710996 61.4777011118527 88.9169964732945 84.2320613854983 69.1622655457769 60.1255829409642 382.758342400691 429.238548268896 3.90087434250685 4.02923006445781 245.047319536046 186.199916603738 4.60503013970163 16.7179032017834 45.8974167676779 58.6091870023334 152.737507677336 87.4646339988696 =================================================== "10_1195.1E.R119U.CEL" "9_C101.1F.R9F2L.CEL" --------------------------------------------- 34.9453663026134 4.35753552341506 120.903734762231 116.962904914229 111.293345773408 133.421207928372 2.96910233809292 14.4050686356057 34.7269027797637 35.8835240852081 85.3109066158579 45.2284068764267 222.081465596656 201.346914814921 378.991271676870 336.282180468649 324.355847430672 337.586327159885 148.252162519851 107.763579952789 146.760939437243 127.027138121574 68.9112298899552 45.5584187250637 178.300028533109 125.831740523771 457.092497175424 331.253094567131 349.374485133996 357.721065463285 8.39630366380937 4.30526177658911 50.2501294702745 31.1539961383794 51.2772385586404 66.8937884059372 169.473350033569 117.993461506227 47.5601861370703 41.0301951390256 238.568680512591 271.103448196271 122.668905036686 92.7991203760259 710.506330695352 568.473304793075 14.1193442910318 11.2664752571536 29.6858453280301 41.0915584209232 78.9811024872745 98.557906977124 143.137824860583 200.312672914717 228.952312559228 208.952150636992 414.93711559597 364.157958616779 193.573470074735 156.743939369768 151.710594739511 165.182915986475 16.3790389361525 62.1220611327726 63.6344501007354 81.4281142367824 52.6876908746722 58.4074520261634 356.890313613082 426.263965724419 4.0847500724139 4.13161532597561 233.32353554667 185.840713238473 4.71348339142599 16.7565881676473 89.4105877815801 55.7427731671095 162.930238504639 91.1574660327713 27.6720869896949 30.8456197258235 107.041950691333 17.5365838616139 132.491703246086 94.8472761626705 165.348305450273 118.806052283819 428.453296492502 438.259964898252 38.5832188166168 20.0643402347992 -- Sucheta Tripathy, Ph.D. Virginia Bioinformatics Institute Phase-I Washington street. Virginia Tech. Blacksburg,VA 24061-0447 phone:(540)231-8138 Fax: (540) 231-2606 web page: http://staff.vbi.vt.edu/sutripa blog : http://genomics-array.blogspot.com/ quick ref: http://faculty.ucr.edu/~tgirke/Documents/R_BioCond/R_BioCondManual.htm l

Sucheta Tripathy wrote: > Dear Group > > when I run background(using GCRMA) correction for chips: > > "10_1331.1I.R208L.CEL" "9_C101.1F.R9F2L.CEL" and for chips > "10_1195.1E.R119U.CEL" "9_C101.1F.R9F2L.CEL" keeping > 9_C101.1F.R9F2L.CEL as constant, For both the runs I get slightly > different outputs for chip 9_C101.1F.R9F2L.CEL (Data below). This does not > happen when GSB.adjust is set to FALSE. Also we have noticed the variation > seem to get lesser when we try more chips together.Any reason why it > should be happening this way? I would recommend reading (or re-reading) the GCRMA papers by Wu and Irizarry that can be found on Rafael Irizarry's website. The question you pose indicates a fundamental lack of knowledge about the procedure you are using, which can be dangerous, especially since you appear to want to do some non-standard things. Anyway, the short answer is that the background is based on a model fit using the MM probes (from all chips in the data set). If you vary what chips you are using, by definition the background estimates will change. In addition, as with all models, the more data you have, the better and more stable the estimates, so more chips == better and more stable background estimates. Best, Jim > > Many thanks > > Sucheta > > My code: > ------- > obj<-ReadAffy(filenames=file) > tmp1<-bg.adjust.gcrma(obj,optical.correct=T,affinity.info=affinfo) > outfile<-paste(outdir, celfile[i,1], "_bg.txt", sep="") > write.table(pm(tmp1), file=outfile, row.names=FALSE, col.names=TRUE, > sep="\t") > ---------------------------------------------------------------------- > > > "10_1331.1I.R208L.CEL" "9_C101.1F.R9F2L.CEL" > --------------------------------------------- > 12.5854077145271 4.27009199115734 > 135.577788495271 115.177321956904 > 113.171763014501 124.781182045557 > 2.69508615100678 13.3527712251500 > 14.5462397159524 36.7662738574386 > 94.6480456343775 48.972931999473 > 230.750229599019 212.534925776574 > 242.058765502072 337.251490520153 > 233.871977591185 339.413283090951 > 134.355125363486 108.047618775561 > 136.685235380017 126.239703801863 > 76.2625488684543 45.3623158856175 > 148.251139760089 120.315265011794 > 328.121529159736 319.366509787047 > 291.865380794849 361.992073209429 > 3.97218796139000 4.20902848830535 > 14.6419514021341 31.6450267847893 > 28.8699339528603 67.3237575282198 > 110.496037483661 111.806067290232 > 22.2876523362755 41.5481196151883 > 205.194483921088 276.995029856902 > 84.8559677803056 96.0077121491932 > 778.222646971625 559.863168099135 > 4.83202857118797 11.3149613102092 > 3.66166154528273 39.6717762417948 > 67.7761672656053 94.6394189279102 > 112.500673213605 190.985739398352 > 171.007645212454 200.035151512867 > 492.236603432973 352.584270678829 > 130.800353580651 155.324195356517 > 146.303381286542 160.442554666605 > 4.34069757710996 61.4777011118527 > 88.9169964732945 84.2320613854983 > 69.1622655457769 60.1255829409642 > 382.758342400691 429.238548268896 > 3.90087434250685 4.02923006445781 > 245.047319536046 186.199916603738 > 4.60503013970163 16.7179032017834 > 45.8974167676779 58.6091870023334 > 152.737507677336 87.4646339988696 > =================================================== > > "10_1195.1E.R119U.CEL" "9_C101.1F.R9F2L.CEL" > --------------------------------------------- > 34.9453663026134 4.35753552341506 > 120.903734762231 116.962904914229 > 111.293345773408 133.421207928372 > 2.96910233809292 14.4050686356057 > 34.7269027797637 35.8835240852081 > 85.3109066158579 45.2284068764267 > 222.081465596656 201.346914814921 > 378.991271676870 336.282180468649 > 324.355847430672 337.586327159885 > 148.252162519851 107.763579952789 > 146.760939437243 127.027138121574 > 68.9112298899552 45.5584187250637 > 178.300028533109 125.831740523771 > 457.092497175424 331.253094567131 > 349.374485133996 357.721065463285 > 8.39630366380937 4.30526177658911 > 50.2501294702745 31.1539961383794 > 51.2772385586404 66.8937884059372 > 169.473350033569 117.993461506227 > 47.5601861370703 41.0301951390256 > 238.568680512591 271.103448196271 > 122.668905036686 92.7991203760259 > 710.506330695352 568.473304793075 > 14.1193442910318 11.2664752571536 > 29.6858453280301 41.0915584209232 > 78.9811024872745 98.557906977124 > 143.137824860583 200.312672914717 > 228.952312559228 208.952150636992 > 414.93711559597 364.157958616779 > 193.573470074735 156.743939369768 > 151.710594739511 165.182915986475 > 16.3790389361525 62.1220611327726 > 63.6344501007354 81.4281142367824 > 52.6876908746722 58.4074520261634 > 356.890313613082 426.263965724419 > 4.0847500724139 4.13161532597561 > 233.32353554667 185.840713238473 > 4.71348339142599 16.7565881676473 > 89.4105877815801 55.7427731671095 > 162.930238504639 91.1574660327713 > 27.6720869896949 30.8456197258235 > 107.041950691333 17.5365838616139 > 132.491703246086 94.8472761626705 > 165.348305450273 118.806052283819 > 428.453296492502 438.259964898252 > 38.5832188166168 20.0643402347992 > -- James W. MacDonald, M.S. Biostatistician Affymetrix and cDNA Microarray Core University of Michigan Cancer Center 1500 E. Medical Center Drive 7410 CCGC Ann Arbor MI 48109 734-647-5623 ********************************************************** Electronic Mail is not secure, may not be read every day, and should not be used for urgent or sensitive issues.