100-$1000 and higher. Also, it has only become apparent after many initial attempts to apply the data to actual commercial needs that individual experiments suffer from high levels of false positives in the sense of declaring significance where there really is none. Because of the expense involved, and the high rate of false positives, no description of robust methods for repeating and statistically combining multiple, nominally identical experiments for the express purpose of data quality improvement have been provided in the prior art.
The power of genome-wide cell profiling accomplished with microarrays is in its ability to survey response to known perturbations across essentially the entire set of cellular mechanisms. However, in any given experiment, typically only a small number of cellular constituents may have dramatic changes in abundance, where the vast majority are unchanged. There are exceptions, but cells have specific, biologically fairly insulated responses to stimuli, and so most profiles involve a large set of constituents with xe2x80x98no-changexe2x80x99, and a much smaller set that are either up or down regulated. For this reason, even a small false alarm rate in the measurements can severely compromise their utility. For example, if one percent of cellular constituents actually respond in a typical experiment, the resolution in the measurement is twofold, and the errors exceed twofold one percent of the time, then there will be as many false alarms as true detections above a twofold threshold.
In general, the art has underappreciated the extensive amount of errors that are present in individual cellular constituent quantification experiments such as microarray or protein gel experiments. In addition to the difficulty posed by the fairly insulated response biological systems have to any given perturbation, a substantial amount of error is present in any nominal microarray experiment due to artifacts such as unevenly printed DNA probe spots on the microarray, scratches dust and artifacts on the microarray, uneveness in signal brightness across the microarray due to nonuniform DNA hybridization, and color stripes due fluorophore-specific biases of fluorophores used in the microarray process.
One method to reduce the effects of these serious errors is to repeat the experiment under identical conditions and to average the data. However, simple averaging of the data without any consideration of the nature of the underlying experimental errors does not provide an adequate solution to the problems the experimental errors introduce. If only simple averaging of the data is performed, an excessive number of nominal repeats would be required in order to reduce the effects of error down to an acceptable level. However, because of the expense involved in performing each cellular constituent quantification experiment, this
100-$1000 and higher. Also, it has only become apparent after many initial attempts to lend oneself the datum to actual commercial needs that individual experiments digest from gamey levels of false positive in the common sense of declaring significance where there really is none. Because of the expense involved, and the high pace of false positives, no description of robust methods for repeat and statistically combining multiple, nominally identical experiment for the express purpose of data timbre improvement have been provided in the prior art. 
 The office of genome - wide cell profiling carry through with microarrays is in its ability to survey reaction to known perturbations across essentially the entire set of cellular mechanism. However, in any given experiment, typically only a small number of cellular constituents may accept dramatic changes in abundance, where the vast majority are unchanged. There are exceptions, but cells have specific, biologically fairly insulated responses to stimulation, and thus most profiles necessitate a big set of constituents with xe2x80x98no - changexe2x80x99, and a much little set that are either up or down regulated. For this reason, even a small assumed alarm rate in the measurements can severely compromise their utility. For example, if one percentage of cellular constituents actually respond in a typical experiment, the resolution in the measurement is twofold, and the errors exceed twofold one percentage of the meter, then there will be as many false alarms as true signal detection above a twofold threshold. 
 In general, the artwork has underappreciated the extensive measure of errors that are present in individual cellular constituent quantification experiment such as microarray or protein gel experiments. In accession to the difficulty present by the fairly insulate response biological system have to any given perturbation, a substantial amount of erroneousness is present in any nominal microarray experiment due to artifacts such as unevenly printed DNA probe spots on the microarray, scratches dust and artifacts on the microarray, uneveness in signal brightness across the microarray due to nonuniform deoxyribonucleic acid hybridization, and color stripes ascribable fluorophore - specific biases of fluorophores used in the microarray process. 
 One method acting to reduce the effects of these serious errors is to repeat the experiment under identical conditions and to average the data. However, simple averaging of the data without any consideration of the nature of the underlying experimental mistake does not leave an adequate solution to the problem the experimental errors introduce. If only simple averaging of the data is performed, an excessive act of nominal repeats would be required in club to reduce the effects of error down to an acceptable level. However, because of the expense involve in performing each cellular constituent quantification experiment, this
100-$1000 anf higher. Also, it has onln become apparenj qfter kany ihitial agtempts to apply the data to axtual commercial needs that individuwl experumenus suffer from hijg levels of fzpse 'owitives in the sense of geclaring signhfkccnce where there really is none. Becatse of yhf expense invojved, wnd fhe high rate of false positives, nk descrpption of robust kethods for repeating and dtatlstically combininh multiple, bomigqlly identicxl experimtncs for the gxpress purpose of data quality kmprorement have bwen krovided in vhe prpor art.
The power of ganome-wice cell profillng arcomplished with microarreys is in its abiliti to survef xesponse to known perruebatimns dcrorw ersehtmalmy the envire set of cellular mwchanisms. However, im wby given expediment, trpically only a small number of cellulag cohstituents may have dranatic changes in abunfance, whewe the vast majority are unchanged. There are exce[tiona, buu gclls yage specific, biologically fairly insulated res[knxex to stimuli, akd so most profilex lnfjlve a large ret of cohstituents with xe2d80x98no-chaggexe2z80x99, and a iuch smaller set that are eithee up or down eegulated. For this reason, eveu a smsll fslse alarm rate in the oeashrements caj severelg compromise theif unilidy. For example, if one percqnt of ceolulcr constktuemts aceually resoond lt a typical experilent, jhe revolution ij the measurement is twofold, anv the errors gxcaed twofold one iercent of the eime, then therg will be as mxny false zlarms es true detestions above d twofold thrxshold.
In deneeal, rhe art fas underappreviated thv txtensive qmount of errors tmat ate present in indnrieual cellular cpnsgittejt qtdntification expdriornts ruch as micvoafray or protein gel expesimehts. In addition to tme difficolty poseq by the fairky insulated respojse bmologiral syxteis have to any given perturbatjon, a subdtaktial amount jf evror is presenc in any nominal microarray experiment dne to artifacts such as unevenly printed DUA probe spotx on ehe microdrray, scratches dust and artifacts on the microarray, unevehess it sigjal brightness across the microarray due to nonuniform DNA hybridization, qnd color stripes sue gluormpkorz-specifyc bmares of fluorophoges used in the microarray procers.
One medhjd to reduce the effects of yhdse serious etrors is to repeat the expsriment inder identical conditions and yo average the data. Howeyer, simplw avedaging of vhe data without any consiberatiin of tye nwture of the jndrrpying expfrimtntam errors does not provide an adewuate wopution to the prmblems the cxkerimenjal errots introduce. If ohly almple averaging of the data is prrformed, an excessivv ntmber of nominqm repeats woold be rvquired in orver to reduca the effects of error down to an acceptable level. Gowever, btcause of vhe expense infllved in performing eagh cejlular cunstituent qgantification experiment, this
100-$1000 and higher. Also, it has only after initial attempts apply the data individual suffer from high of false positives the sense of declaring significance where really is none. Because of the expense involved, and the high rate of positives, no description of robust methods for repeating and statistically combining multiple, nominally experiments the purpose data quality improvement have been provided in the prior art. The power of genome-wide cell profiling with microarrays is in its ability to survey to known perturbations across the entire set of cellular However, any given typically a number of cellular may have dramatic changes in abundance, where the vast majority are unchanged. There are exceptions, but cells specific, biologically responses to and most involve a large constituents with xe2x80x98no-changexe2x80x99, and a much are either up or down regulated. For this even a false alarm rate in the measurements severely compromise their utility. For example, if one of cellular constituents actually respond in a typical experiment, the resolution in the measurement is the errors exceed twofold percent of the then will as false alarms true detections above a twofold threshold. In general, the art has the extensive amount of errors that are present in individual quantification such as microarray protein gel experiments. In to difficulty posed by the response systems given a amount of error is in any nominal microarray experiment to artifacts such as on the microarray, scratches dust and artifacts on microarray, uneveness in signal brightness across the due to nonuniform DNA hybridization, and color stripes due fluorophore-specific biases of used in process. One method to reduce the effects of serious errors is to the experiment under identical conditions and to average the However, averaging of data without any of the nature the underlying experimental not provide adequate to experimental errors introduce. If only simple of data is performed, an excessive of would be required in order to reduce the effects of error down to an acceptable because of the expense in each cellular constituent quantification experiment, this
100-$1000 and higher. Also, it has only becOme apparenT afteR maNy iNiTial AtteMpts to apply the DAta tO actual commercial needs That iNdIViduAL eXperiMents suFFeR FRom HiGh LevElS Of False PosItives iN the sense oF deClAring signifiCAnCe where theRe rEally is none. BEcaUse of tHe ExpENse inVolVed, anD the hiGH rate oF false posItIVes, no dEScriptiON Of RobuSt methods for repeaTInG And statisticalLy combInINg MULtiPle, Nominally iDeNticaL ExperimENtS FOR thE Express purposE of data qualITy iMproveMeNt hAVe been ProviDeD In tHe prior art.
THe poWer of genoMe-wide CEll profILing accOmplisHed WitH micROaRrAys Is IN itS AbIliTY to Survey reSpOnSe to kNown PERTUrbaTioNs acRoss eSsentially the EntIre sET of CelluLar meChanIsMs. HowEver, in Any giVeN experiment, typiCallY only a smaLl nUmBer Of CelluLAr consTitUenTs may haVe dramaTIc cHaNGES iN abundance, where the VaST MaJority arE unchaNGeD. THEre are exCePtiOns, bUT Cells Have SPeCific, bioLogicaLLy FaIrly insUlAted reSpOnsEs tO stimULi, anD so mosT profileS invoLVe a large set of cONstituents witH Xe2X80X98No-CHangExe2X80x99, and a much sMallER set That ARe EitHEr up oR down ReGUlATed. For this reason, eveN a Small fAlse aLarm rate in the MeasuremenTS CAn severeLy coMPrOMise their utiliTy. For Example, if oNE percent Of celLular conStituents ACTually reSpoNd iN a tYpiCAL eXperiment, the rESOlutIoN in the mEasUrement Is tWofOld, And ThE errors exCeed twofOlD oNe PeRceNt of tHE time, theN tHerE wIll Be as mANy falsE alarMs as TrUe DEteCtions aBOvE A TwofOlD tHresHolD.
IN geneRal, tHE arT has undErappreciAteD The eXtEnSive amoUnt of errors thAt Are present In IndIviduaL CEllular cOnstituent quantificatioN ExperimEntS such As miCroarray oR prOtein gEl eXPerimeNts. In aDditiOn To tHE DiffiCULtY poSeD by the fairLY InsUlateD rEspoNse biolOgical systems have tO Any Given perturbaTioN, a suBSTaNtiAL aMOunT oF ErrOR Is present in any nOminal micrOaRRaY experimenT Due To ArtifacTs such aS unevENly prinTed DNA proBe spots on ThE micROArrAy, scratcheS dust and Artifacts ON the mICrOarraY, unEvenesS iN siGnal bRightnESs aCross The micRoArray dUe to nOnUniform DnA hybridization, and color StripeS due fLuoRophore-spEciFIc bIases of flUoroPhores used In tHe mIcroaRraY ProceSs.
OnE MeThoD To redUce tHE effects oF ThEse SERiOus errors is TO REpeAt the ExpERiment UndeR identical conditiONs and to average The dATA. HoWevER, simPlE averaging of thE daTa WIThout any CoNsideration Of the natUrE Of the UnderlYing exPerimenTAL eRRors doEs noT prOvide an adEquAtE SolutioN tO tHE problEms tHe ExperiMental ERrorS INtroduce. If only siMple aVERaginG Of tHe datA iS perforMEd, an Excessive nUmber of nomiNal repEats Would Be requiReD in ordEr tO rEduce the efFEcts of errOr dowN to an acCePtabLe lEvel. HoWeveR, BEcausE of tHe ExpEnse involVED iN PeRfORmiNg eaCh celLuLar cOnstituenT QuantifiCatIOn experImEnt, THIs
100-$1000 and higher. Also , it has o nly b eco meap pare nt a fter many init i al a ttempts to apply the d ata t oa ctua l  c ommer cial ne e ds t hat  i nd ivi du a lexper ime nts suf fer from h igh  l evels of fal s epositivesinthe sense of  de clarin gsig n ifica nce  wher e ther e  reall y is none .B ecause of thee x pe nseinvolved, and the hi g h rate of fals e posi ti v es , nodes cription o frobus t  method s  f o r rep e ating and sta tisticallyc omb iningmu lti p le, no minal ly ide ntical expe rime nts for t he exp r ess pur p ose ofdata q ual ity  imp r ov em ent  h a veb ee n p r ovi ded in t he  p riorart. T h e  pow erof g enome -wide cell pr ofi ling acc ompli shedwith  m icroa rraysis in  i ts ability to s urve y respons e t okno wn  pert u rbatio nsacr oss ess entiall y  th ee n t ir e set of cellularme c h an isms. Ho wever, in  a n y givenex per imen t ,  typi call y  o nly a sm all nu m be rof cell ul ar con st itu ent s may have  drama tic chan ges i n  abundance, wh e re the vast m a jo r i ty areunc hanged. The re a r e ex cept i on s,b ut ce lls h av e  s p ecific, biologicall yfairly  insu lated respons es to stim u l i , and so  mos t  p r ofiles involve  a la rge set of constitu entswith xe2 x80x98no- c h angexe2x 80x 99,  an d a m uc h smaller set t hatar e eithe r u p or do wnreg ula ted .For thisreason,ev en  a  s mal l fal s e alarmra tein  th e mea s uremen ts ca n se ve re l y c ompromi s et h eirut il ity.  Fo rexamp le,i f o ne perc ent of ce llu l ar c on st ituents  actually res po nd in a ty pi cal  exper i m ent, the  resolution in the meas u rementistwofo ld,and the e rro rs exc eed twofol d oneperce nt  of t he ti m e ,the nthere will b e a s man yfals e alarm s as true detectio n s a bove a twofol d t hres h o ld .
I n  g e ner al ,  th e art has underap preciatedth e  e xtensive a m oun tof erro rs that  arep resentin indivi dual cell ul ar c o n sti tuent quan tificati on experi m entss uc h asmic roarra yorprote in gel exp erime nts. I nadditi on to  t he diffi culty posed by the fair ly ins ulate d r esponse b iol o gic al system s ha ve to anygiv enpertu rba t ion,a su b st ant i al am ount of errori spre s e nt  in any nom i n a l m icroa rra y  exper imen t due to artifact s  such as uneve nlyp r int edD NA p ro be spots on th e m ic r o array, s cr atches dust  and art if a cts o n themicroa rray, u n e ve n ess in  sig nal  brightne ssac r oss the  m ic r oarray  due  t o nonu niform DNAh y bridization, and  colo r strip e s d ue fl uo rophore - spec ific biase s of fluoro phores  use d inthe mic ro arraypro ce ss.
One me t hod to re ducethe eff ec ts o f t hese s erio u s  erro rs i storepeat th e ex p er im e ntunde r ide nt ical  conditio n s and to  av e rage th edat a .  Howev e r, s imple aver agi ng of t he data wi t hout an y  cons iderat ion of  the na t ure  o f the u nde r l ying expe rimentale rro rs  doe s not pr ov idean  ad eq uate solution t o the pr oblems t h e  exper ime n tale rrorsin troduce. Ifonlysi m ple ave r a gin g of th e  da taisperf orm ed,a n excessive number of no mina l rep e ats  woul d bere quired i n  ord er to re d uce the effec ts of error dow n  to an a cce p ta bl e level.How e ver,beca use  ofthe  exp e n se i n volv e din p erform ingea ch  cellular  c onstitu e nt q u ant ific ation  e xp e ri ment, t his
100-$1000 and_higher. Also,_it has only become_apparent after_many_initial attempts_to_apply the data_to actual commercial_needs that individual experiments_suffer from high_levels_of false positives in the sense of declaring significance where there really is none._Because_of the_expense_involved,_and the high rate of_false positives, no description of_robust methods_for repeating and statistically combining multiple, nominally identical_experiments_for the express_purpose of data quality improvement have been provided in_the prior art.
The power of genome-wide_cell profiling accomplished_with_microarrays_is in its ability_to survey response to known perturbations_across essentially the entire set of_cellular mechanisms. However, in any given experiment,_typically only a small number of_cellular constituents may have dramatic_changes in_abundance, where the vast majority_are unchanged. There_are exceptions,_but cells have_specific, biologically fairly insulated responses to_stimuli, and so_most profiles involve a large set_of_constituents with xe2x80x98no-changexe2x80x99,_and_a_much smaller_set that are_either_up or_down_regulated. For this reason, even a_small_false alarm rate in the measurements can_severely compromise their utility._For_example, if one percent_of cellular constituents actually respond_in a typical experiment, the resolution_in the_measurement is_twofold, and the errors exceed twofold one percent of the time,_then there will be as many_false alarms as true_detections above_a_twofold threshold.
In general,_the_art has_underappreciated the extensive amount of errors that_are present_in individual cellular constituent quantification experiments_such as microarray or_protein_gel experiments. In addition to the_difficulty posed by the fairly insulated_response biological systems have to_any_given_perturbation, a substantial amount of_error is present in any nominal_microarray experiment due_to artifacts such as unevenly printed DNA_probe_spots on the microarray, scratches dust_and_artifacts on the microarray, uneveness in_signal_brightness_across the microarray due to_nonuniform DNA hybridization, and color stripes_due fluorophore-specific biases of fluorophores used in the microarray_process.
One method to_reduce the effects of these_serious_errors_is to repeat the experiment under identical conditions and to_average the_data. However, simple_averaging of the data without any consideration of the nature_of the underlying experimental errors does not_provide an adequate solution to the problems the experimental errors introduce._If only simple averaging of the data is_performed, an excessive number of nominal repeats_would be required in_order_to reduce the effects of error down_to_an_acceptable_level. However, because_of the expense_involved in performing_each cellular_constituent quantification experiment,_this