Standardizing global gene expression analysis between laboratories and across platforms.

Theodore Bammler, Richard P. Beyer, Sanchita Bhattacharya, Gary A. Boorman, Abee Boyles, Blair U. Bradford, Roger E. Bumgarner, Pierre R. Bushel, Kabir Chaturvedi, Dongseok Choi, Michael L. Cunningham, Shibing Deng, Holly K. Dressman, Rickie D. Fannin, Fredrico M. Farin, Jonathan H. Freedman, Rebecca C. Fry, Angel Harper, Michael C. Humble, Patrick Hurban & 44 others Terrance J. Kavanagh, William K. Kaufmann, Kathleen F. Kerr, L. Jing, Jodi Lapidus, Michael R. Lasarev, Jianying Li, Yi Ju Li, Edward K. Lobenhofer, Xinfang Lu, Renae L. Malek, Sean Milton, Srinivasa R. Nagalla, Jean P. O'malley, Valerie Palmer, Patrick Pattee, Richard S. Paules, Charles M. Perou, Ken Phillips, Li Xuan Qin, Yang Qiu, Sean D. Quigley, Matthew Rodland, Ivan Rusyn, Leona D. Samson, David A. Schwartz, Yan Shi, Jung Lim Shin, Stella O. Sieber, Susan Slifer, Marcy C. Speer, Peter Spencer, Dean I. Sproles, James A. Swenberg, William A. Suk, Robert C. Sullivan, R. Tian, Raymond W. Tennant, Signe A. Todd, Charles J. Tucker, Bennett Van Houten, Brenda K. Weis, Shirley Xuan, Helmut Zarbl

Research output: Contribution to journalArticle

383 Citations (Scopus)

Abstract

To facilitate collaborative research efforts between multi-investigator teams using DNA microarrays, we identified sources of error and data variability between laboratories and across microarray platforms, and methods to accommodate this variability. RNA expression data were generated in seven laboratories, which compared two standard RNA samples using 12 microarray platforms. At least two standard microarray types (one spotted, one commercial) were used by all laboratories. Reproducibility for most platforms within any laboratory was typically good, but reproducibility between platforms and across laboratories was generally poor. Reproducibility between laboratories increased markedly when standardized protocols were implemented for RNA labeling, hybridization, microarray processing, data acquisition and data normalization. Reproducibility was highest when analysis was based on biological themes defined by enriched Gene Ontology (GO) categories. These findings indicate that microarray results can be comparable across multiple laboratories, especially when a common platform and set of procedures are used.

Original languageEnglish (US)
Pages (from-to)351-356
Number of pages6
JournalNat Methods
Volume2
Issue number5
StatePublished - May 2005

Fingerprint

Gene expression
Microarrays
Gene Expression
RNA
Gene Ontology
Information Storage and Retrieval
Oligonucleotide Array Sequence Analysis
Labeling
Ontology
Data acquisition
Research Design
Genes
Research Personnel
Network protocols
DNA
Research

ASJC Scopus subject areas

  • Biotechnology
  • Molecular Biology
  • Cell Biology

Cite this

Bammler, T., Beyer, R. P., Bhattacharya, S., Boorman, G. A., Boyles, A., Bradford, B. U., ... Zarbl, H. (2005). Standardizing global gene expression analysis between laboratories and across platforms. Nat Methods, 2(5), 351-356.

Standardizing global gene expression analysis between laboratories and across platforms. / Bammler, Theodore; Beyer, Richard P.; Bhattacharya, Sanchita; Boorman, Gary A.; Boyles, Abee; Bradford, Blair U.; Bumgarner, Roger E.; Bushel, Pierre R.; Chaturvedi, Kabir; Choi, Dongseok; Cunningham, Michael L.; Deng, Shibing; Dressman, Holly K.; Fannin, Rickie D.; Farin, Fredrico M.; Freedman, Jonathan H.; Fry, Rebecca C.; Harper, Angel; Humble, Michael C.; Hurban, Patrick; Kavanagh, Terrance J.; Kaufmann, William K.; Kerr, Kathleen F.; Jing, L.; Lapidus, Jodi; Lasarev, Michael R.; Li, Jianying; Li, Yi Ju; Lobenhofer, Edward K.; Lu, Xinfang; Malek, Renae L.; Milton, Sean; Nagalla, Srinivasa R.; O'malley, Jean P.; Palmer, Valerie; Pattee, Patrick; Paules, Richard S.; Perou, Charles M.; Phillips, Ken; Qin, Li Xuan; Qiu, Yang; Quigley, Sean D.; Rodland, Matthew; Rusyn, Ivan; Samson, Leona D.; Schwartz, David A.; Shi, Yan; Shin, Jung Lim; Sieber, Stella O.; Slifer, Susan; Speer, Marcy C.; Spencer, Peter; Sproles, Dean I.; Swenberg, James A.; Suk, William A.; Sullivan, Robert C.; Tian, R.; Tennant, Raymond W.; Todd, Signe A.; Tucker, Charles J.; Van Houten, Bennett; Weis, Brenda K.; Xuan, Shirley; Zarbl, Helmut.

In: Nat Methods, Vol. 2, No. 5, 05.2005, p. 351-356.

Research output: Contribution to journalArticle

Bammler, T, Beyer, RP, Bhattacharya, S, Boorman, GA, Boyles, A, Bradford, BU, Bumgarner, RE, Bushel, PR, Chaturvedi, K, Choi, D, Cunningham, ML, Deng, S, Dressman, HK, Fannin, RD, Farin, FM, Freedman, JH, Fry, RC, Harper, A, Humble, MC, Hurban, P, Kavanagh, TJ, Kaufmann, WK, Kerr, KF, Jing, L, Lapidus, J, Lasarev, MR, Li, J, Li, YJ, Lobenhofer, EK, Lu, X, Malek, RL, Milton, S, Nagalla, SR, O'malley, JP, Palmer, V, Pattee, P, Paules, RS, Perou, CM, Phillips, K, Qin, LX, Qiu, Y, Quigley, SD, Rodland, M, Rusyn, I, Samson, LD, Schwartz, DA, Shi, Y, Shin, JL, Sieber, SO, Slifer, S, Speer, MC, Spencer, P, Sproles, DI, Swenberg, JA, Suk, WA, Sullivan, RC, Tian, R, Tennant, RW, Todd, SA, Tucker, CJ, Van Houten, B, Weis, BK, Xuan, S & Zarbl, H 2005, 'Standardizing global gene expression analysis between laboratories and across platforms.', Nat Methods, vol. 2, no. 5, pp. 351-356.
Bammler T, Beyer RP, Bhattacharya S, Boorman GA, Boyles A, Bradford BU et al. Standardizing global gene expression analysis between laboratories and across platforms. Nat Methods. 2005 May;2(5):351-356.
Bammler, Theodore ; Beyer, Richard P. ; Bhattacharya, Sanchita ; Boorman, Gary A. ; Boyles, Abee ; Bradford, Blair U. ; Bumgarner, Roger E. ; Bushel, Pierre R. ; Chaturvedi, Kabir ; Choi, Dongseok ; Cunningham, Michael L. ; Deng, Shibing ; Dressman, Holly K. ; Fannin, Rickie D. ; Farin, Fredrico M. ; Freedman, Jonathan H. ; Fry, Rebecca C. ; Harper, Angel ; Humble, Michael C. ; Hurban, Patrick ; Kavanagh, Terrance J. ; Kaufmann, William K. ; Kerr, Kathleen F. ; Jing, L. ; Lapidus, Jodi ; Lasarev, Michael R. ; Li, Jianying ; Li, Yi Ju ; Lobenhofer, Edward K. ; Lu, Xinfang ; Malek, Renae L. ; Milton, Sean ; Nagalla, Srinivasa R. ; O'malley, Jean P. ; Palmer, Valerie ; Pattee, Patrick ; Paules, Richard S. ; Perou, Charles M. ; Phillips, Ken ; Qin, Li Xuan ; Qiu, Yang ; Quigley, Sean D. ; Rodland, Matthew ; Rusyn, Ivan ; Samson, Leona D. ; Schwartz, David A. ; Shi, Yan ; Shin, Jung Lim ; Sieber, Stella O. ; Slifer, Susan ; Speer, Marcy C. ; Spencer, Peter ; Sproles, Dean I. ; Swenberg, James A. ; Suk, William A. ; Sullivan, Robert C. ; Tian, R. ; Tennant, Raymond W. ; Todd, Signe A. ; Tucker, Charles J. ; Van Houten, Bennett ; Weis, Brenda K. ; Xuan, Shirley ; Zarbl, Helmut. / Standardizing global gene expression analysis between laboratories and across platforms. In: Nat Methods. 2005 ; Vol. 2, No. 5. pp. 351-356.
@article{ef3212fe1ab64f2887e5c018f60c47c1,
title = "Standardizing global gene expression analysis between laboratories and across platforms.",
abstract = "To facilitate collaborative research efforts between multi-investigator teams using DNA microarrays, we identified sources of error and data variability between laboratories and across microarray platforms, and methods to accommodate this variability. RNA expression data were generated in seven laboratories, which compared two standard RNA samples using 12 microarray platforms. At least two standard microarray types (one spotted, one commercial) were used by all laboratories. Reproducibility for most platforms within any laboratory was typically good, but reproducibility between platforms and across laboratories was generally poor. Reproducibility between laboratories increased markedly when standardized protocols were implemented for RNA labeling, hybridization, microarray processing, data acquisition and data normalization. Reproducibility was highest when analysis was based on biological themes defined by enriched Gene Ontology (GO) categories. These findings indicate that microarray results can be comparable across multiple laboratories, especially when a common platform and set of procedures are used.",
author = "Theodore Bammler and Beyer, {Richard P.} and Sanchita Bhattacharya and Boorman, {Gary A.} and Abee Boyles and Bradford, {Blair U.} and Bumgarner, {Roger E.} and Bushel, {Pierre R.} and Kabir Chaturvedi and Dongseok Choi and Cunningham, {Michael L.} and Shibing Deng and Dressman, {Holly K.} and Fannin, {Rickie D.} and Farin, {Fredrico M.} and Freedman, {Jonathan H.} and Fry, {Rebecca C.} and Angel Harper and Humble, {Michael C.} and Patrick Hurban and Kavanagh, {Terrance J.} and Kaufmann, {William K.} and Kerr, {Kathleen F.} and L. Jing and Jodi Lapidus and Lasarev, {Michael R.} and Jianying Li and Li, {Yi Ju} and Lobenhofer, {Edward K.} and Xinfang Lu and Malek, {Renae L.} and Sean Milton and Nagalla, {Srinivasa R.} and O'malley, {Jean P.} and Valerie Palmer and Patrick Pattee and Paules, {Richard S.} and Perou, {Charles M.} and Ken Phillips and Qin, {Li Xuan} and Yang Qiu and Quigley, {Sean D.} and Matthew Rodland and Ivan Rusyn and Samson, {Leona D.} and Schwartz, {David A.} and Yan Shi and Shin, {Jung Lim} and Sieber, {Stella O.} and Susan Slifer and Speer, {Marcy C.} and Peter Spencer and Sproles, {Dean I.} and Swenberg, {James A.} and Suk, {William A.} and Sullivan, {Robert C.} and R. Tian and Tennant, {Raymond W.} and Todd, {Signe A.} and Tucker, {Charles J.} and {Van Houten}, Bennett and Weis, {Brenda K.} and Shirley Xuan and Helmut Zarbl",
year = "2005",
month = "5",
language = "English (US)",
volume = "2",
pages = "351--356",
journal = "PLoS Medicine",
issn = "1549-1277",
publisher = "Nature Publishing Group",
number = "5",

}

TY - JOUR

T1 - Standardizing global gene expression analysis between laboratories and across platforms.

AU - Bammler, Theodore

AU - Beyer, Richard P.

AU - Bhattacharya, Sanchita

AU - Boorman, Gary A.

AU - Boyles, Abee

AU - Bradford, Blair U.

AU - Bumgarner, Roger E.

AU - Bushel, Pierre R.

AU - Chaturvedi, Kabir

AU - Choi, Dongseok

AU - Cunningham, Michael L.

AU - Deng, Shibing

AU - Dressman, Holly K.

AU - Fannin, Rickie D.

AU - Farin, Fredrico M.

AU - Freedman, Jonathan H.

AU - Fry, Rebecca C.

AU - Harper, Angel

AU - Humble, Michael C.

AU - Hurban, Patrick

AU - Kavanagh, Terrance J.

AU - Kaufmann, William K.

AU - Kerr, Kathleen F.

AU - Jing, L.

AU - Lapidus, Jodi

AU - Lasarev, Michael R.

AU - Li, Jianying

AU - Li, Yi Ju

AU - Lobenhofer, Edward K.

AU - Lu, Xinfang

AU - Malek, Renae L.

AU - Milton, Sean

AU - Nagalla, Srinivasa R.

AU - O'malley, Jean P.

AU - Palmer, Valerie

AU - Pattee, Patrick

AU - Paules, Richard S.

AU - Perou, Charles M.

AU - Phillips, Ken

AU - Qin, Li Xuan

AU - Qiu, Yang

AU - Quigley, Sean D.

AU - Rodland, Matthew

AU - Rusyn, Ivan

AU - Samson, Leona D.

AU - Schwartz, David A.

AU - Shi, Yan

AU - Shin, Jung Lim

AU - Sieber, Stella O.

AU - Slifer, Susan

AU - Speer, Marcy C.

AU - Spencer, Peter

AU - Sproles, Dean I.

AU - Swenberg, James A.

AU - Suk, William A.

AU - Sullivan, Robert C.

AU - Tian, R.

AU - Tennant, Raymond W.

AU - Todd, Signe A.

AU - Tucker, Charles J.

AU - Van Houten, Bennett

AU - Weis, Brenda K.

AU - Xuan, Shirley

AU - Zarbl, Helmut

PY - 2005/5

Y1 - 2005/5

N2 - To facilitate collaborative research efforts between multi-investigator teams using DNA microarrays, we identified sources of error and data variability between laboratories and across microarray platforms, and methods to accommodate this variability. RNA expression data were generated in seven laboratories, which compared two standard RNA samples using 12 microarray platforms. At least two standard microarray types (one spotted, one commercial) were used by all laboratories. Reproducibility for most platforms within any laboratory was typically good, but reproducibility between platforms and across laboratories was generally poor. Reproducibility between laboratories increased markedly when standardized protocols were implemented for RNA labeling, hybridization, microarray processing, data acquisition and data normalization. Reproducibility was highest when analysis was based on biological themes defined by enriched Gene Ontology (GO) categories. These findings indicate that microarray results can be comparable across multiple laboratories, especially when a common platform and set of procedures are used.

AB - To facilitate collaborative research efforts between multi-investigator teams using DNA microarrays, we identified sources of error and data variability between laboratories and across microarray platforms, and methods to accommodate this variability. RNA expression data were generated in seven laboratories, which compared two standard RNA samples using 12 microarray platforms. At least two standard microarray types (one spotted, one commercial) were used by all laboratories. Reproducibility for most platforms within any laboratory was typically good, but reproducibility between platforms and across laboratories was generally poor. Reproducibility between laboratories increased markedly when standardized protocols were implemented for RNA labeling, hybridization, microarray processing, data acquisition and data normalization. Reproducibility was highest when analysis was based on biological themes defined by enriched Gene Ontology (GO) categories. These findings indicate that microarray results can be comparable across multiple laboratories, especially when a common platform and set of procedures are used.

UR - http://www.scopus.com/inward/record.url?scp=18244389201&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=18244389201&partnerID=8YFLogxK

M3 - Article

VL - 2

SP - 351

EP - 356

JO - PLoS Medicine

JF - PLoS Medicine

SN - 1549-1277

IS - 5

ER -