A framework for the informed normalization of printed microarrays
| dc.contributor.author | van Heerden, Johan | |
| dc.contributor.author | Walford, Sally-Ann | |
| dc.contributor.author | Shen, Arthur | |
| dc.contributor.author | Illing, Nicola | |
| dc.date.accessioned | 2016-01-18T12:05:43Z | |
| dc.date.available | 2016-01-18T12:05:43Z | |
| dc.date.issued | 2007 | |
| dc.date.updated | 2016-01-18T10:17:09Z | |
| dc.description.abstract | Microarray technology has become an essential part of contemporary molecular biological research. An aspect central to any microarray experiment is that of normalization, a form of data processing directed at removing technical noise while preserving biological meaning, thereby allowing for more accurate interpretations of data. The statistics underlying many normalization methods can appear overwhelming to microarray newcomers, a situation which is further compounded by a lack of accessible, non-statistical descriptions of common approaches to normalization. Normalization strategies significantly affect the analytical outcome of a microarray experiment, and consequently it is important that the statistical assumptions underlying normalization algorithms are understood and met before researchers embark upon the processing of raw microarray data. Many of these assumptions pertain only to whole-genome arrays, and are not valid for custom or directed microarrays. A thorough diagnostic evaluation of the nature and extent to which technical noise affects individual arrays is paramount to the success of any chosen normalization strategy. Here we suggest an approach to normalization based on extensive stepwise exploration and diagnostic assessment of data prior to, and after, normalization. Common data visualization and diagnostic approaches are highlighted, followed by descriptions of popular normalization methods, and the underlying assumptions they are based on, within the context of removing general technical artefacts associated with microarray data. | en_ZA |
| dc.identifier.apacitation | van Heerden, J., Walford, S., Shen, A., & Illing, N. (2007). A framework for the informed normalization of printed microarrays. <i>South African Journal of Science</i>, http://hdl.handle.net/11427/16413 | en_ZA |
| dc.identifier.chicagocitation | van Heerden, Johan, Sally-Ann Walford, Arthur Shen, and Nicola Illing "A framework for the informed normalization of printed microarrays." <i>South African Journal of Science</i> (2007) http://hdl.handle.net/11427/16413 | en_ZA |
| dc.identifier.citation | Van Heerden, J., Walford, S. A., Shen, A., & Illing, N. (2007). A framework for the informed normalization of printed microarrays: review article. South African Journal of Science, 103(9 & 10), 381-390. | en_ZA |
| dc.identifier.issn | 0038-2353 | en_ZA |
| dc.identifier.ris | TY - Journal Article AU - van Heerden, Johan AU - Walford, Sally-Ann AU - Shen, Arthur AU - Illing, Nicola AB - Microarray technology has become an essential part of contemporary molecular biological research. An aspect central to any microarray experiment is that of normalization, a form of data processing directed at removing technical noise while preserving biological meaning, thereby allowing for more accurate interpretations of data. The statistics underlying many normalization methods can appear overwhelming to microarray newcomers, a situation which is further compounded by a lack of accessible, non-statistical descriptions of common approaches to normalization. Normalization strategies significantly affect the analytical outcome of a microarray experiment, and consequently it is important that the statistical assumptions underlying normalization algorithms are understood and met before researchers embark upon the processing of raw microarray data. Many of these assumptions pertain only to whole-genome arrays, and are not valid for custom or directed microarrays. A thorough diagnostic evaluation of the nature and extent to which technical noise affects individual arrays is paramount to the success of any chosen normalization strategy. Here we suggest an approach to normalization based on extensive stepwise exploration and diagnostic assessment of data prior to, and after, normalization. Common data visualization and diagnostic approaches are highlighted, followed by descriptions of popular normalization methods, and the underlying assumptions they are based on, within the context of removing general technical artefacts associated with microarray data. DA - 2007 DB - OpenUCT DP - University of Cape Town J1 - South African Journal of Science LK - https://open.uct.ac.za PB - University of Cape Town PY - 2007 SM - 0038-2353 T1 - A framework for the informed normalization of printed microarrays TI - A framework for the informed normalization of printed microarrays UR - http://hdl.handle.net/11427/16413 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/16413 | |
| dc.identifier.vancouvercitation | van Heerden J, Walford S, Shen A, Illing N. A framework for the informed normalization of printed microarrays. South African Journal of Science. 2007; http://hdl.handle.net/11427/16413. | en_ZA |
| dc.language | eng | en_ZA |
| dc.publisher | Academy of Science of South Africa | en_ZA |
| dc.publisher.department | Department of Molecular and Cell Biology | en_ZA |
| dc.publisher.faculty | Faculty of Science | en_ZA |
| dc.publisher.institution | University of Cape Town | |
| dc.rights | Creative Commons Attribution 4.0 International (CC BY 4.0) | * |
| dc.rights.uri | http://creativecommons.org/licenses/by/4.0/ | en_ZA |
| dc.source | South African Journal of Science | en_ZA |
| dc.source.uri | http://www.sajs.co.za/ | |
| dc.title | A framework for the informed normalization of printed microarrays | en_ZA |
| dc.type | Journal Article | en_ZA |
| uct.subject.keywords | Microarray technology | en_ZA |
| uct.subject.keywords | molecular biological research | en_ZA |
| uct.type.filetype | Text | |
| uct.type.filetype | Image | |
| uct.type.publication | Research | en_ZA |
| uct.type.resource | Article | en_ZA |