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OSAT: a tool for sample-to-batch allocations in genomics experiments
BACKGROUND: Batch effect is one type of variability that is not of primary interest but ubiquitous in sizable genomic experiments. To minimize the impact of batch effects, an ideal experiment design should ensure the even distribution of biological groups and confounding factors across batches. Howe...
Autores principales: | , , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
BioMed Central
2012
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3548766/ https://www.ncbi.nlm.nih.gov/pubmed/23228338 http://dx.doi.org/10.1186/1471-2164-13-689 |
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author | Yan, Li Ma, Changxing Wang, Dan Hu, Qiang Qin, Maochun Conroy, Jeffrey M Sucheston, Lara E Ambrosone, Christine B Johnson, Candace S Wang, Jianmin Liu, Song |
author_facet | Yan, Li Ma, Changxing Wang, Dan Hu, Qiang Qin, Maochun Conroy, Jeffrey M Sucheston, Lara E Ambrosone, Christine B Johnson, Candace S Wang, Jianmin Liu, Song |
author_sort | Yan, Li |
collection | PubMed |
description | BACKGROUND: Batch effect is one type of variability that is not of primary interest but ubiquitous in sizable genomic experiments. To minimize the impact of batch effects, an ideal experiment design should ensure the even distribution of biological groups and confounding factors across batches. However, due to the practical complications, the availability of the final collection of samples in genomics study might be unbalanced and incomplete, which, without appropriate attention in sample-to-batch allocation, could lead to drastic batch effects. Therefore, it is necessary to develop effective and handy tool to assign collected samples across batches in an appropriate way in order to minimize the impact of batch effects. RESULTS: We describe OSAT (Optimal Sample Assignment Tool), a bioconductor package designed for automated sample-to-batch allocations in genomics experiments. CONCLUSIONS: OSAT is developed to facilitate the allocation of collected samples to different batches in genomics study. Through optimizing the even distribution of samples in groups of biological interest into different batches, it can reduce the confounding or correlation between batches and the biological variables of interest. It can also optimize the homogeneous distribution of confounding factors across batches. It can handle challenging instances where incomplete and unbalanced sample collections are involved as well as ideally balanced designs. |
format | Online Article Text |
id | pubmed-3548766 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2012 |
publisher | BioMed Central |
record_format | MEDLINE/PubMed |
spelling | pubmed-35487662013-02-04 OSAT: a tool for sample-to-batch allocations in genomics experiments Yan, Li Ma, Changxing Wang, Dan Hu, Qiang Qin, Maochun Conroy, Jeffrey M Sucheston, Lara E Ambrosone, Christine B Johnson, Candace S Wang, Jianmin Liu, Song BMC Genomics Software BACKGROUND: Batch effect is one type of variability that is not of primary interest but ubiquitous in sizable genomic experiments. To minimize the impact of batch effects, an ideal experiment design should ensure the even distribution of biological groups and confounding factors across batches. However, due to the practical complications, the availability of the final collection of samples in genomics study might be unbalanced and incomplete, which, without appropriate attention in sample-to-batch allocation, could lead to drastic batch effects. Therefore, it is necessary to develop effective and handy tool to assign collected samples across batches in an appropriate way in order to minimize the impact of batch effects. RESULTS: We describe OSAT (Optimal Sample Assignment Tool), a bioconductor package designed for automated sample-to-batch allocations in genomics experiments. CONCLUSIONS: OSAT is developed to facilitate the allocation of collected samples to different batches in genomics study. Through optimizing the even distribution of samples in groups of biological interest into different batches, it can reduce the confounding or correlation between batches and the biological variables of interest. It can also optimize the homogeneous distribution of confounding factors across batches. It can handle challenging instances where incomplete and unbalanced sample collections are involved as well as ideally balanced designs. BioMed Central 2012-12-10 /pmc/articles/PMC3548766/ /pubmed/23228338 http://dx.doi.org/10.1186/1471-2164-13-689 Text en Copyright ©2012 Yan et al.; licensee BioMed Central Ltd. http://creativecommons.org/licenses/by/2.0 This is an Open Access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. |
spellingShingle | Software Yan, Li Ma, Changxing Wang, Dan Hu, Qiang Qin, Maochun Conroy, Jeffrey M Sucheston, Lara E Ambrosone, Christine B Johnson, Candace S Wang, Jianmin Liu, Song OSAT: a tool for sample-to-batch allocations in genomics experiments |
title | OSAT: a tool for sample-to-batch allocations in genomics experiments |
title_full | OSAT: a tool for sample-to-batch allocations in genomics experiments |
title_fullStr | OSAT: a tool for sample-to-batch allocations in genomics experiments |
title_full_unstemmed | OSAT: a tool for sample-to-batch allocations in genomics experiments |
title_short | OSAT: a tool for sample-to-batch allocations in genomics experiments |
title_sort | osat: a tool for sample-to-batch allocations in genomics experiments |
topic | Software |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3548766/ https://www.ncbi.nlm.nih.gov/pubmed/23228338 http://dx.doi.org/10.1186/1471-2164-13-689 |
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