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PRECISION.array: An R Package for Benchmarking microRNA Array Data Normalization in the Context of Sample Classification
We present a new R package PRECISION.array for assessing the performance of data normalization methods in connection with methods for sample classification. It includes two microRNA microarray datasets for the same set of tumor samples: a re-sampling-based algorithm for simulating additional paired...
Autores principales: | , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9354575/ https://www.ncbi.nlm.nih.gov/pubmed/35938023 http://dx.doi.org/10.3389/fgene.2022.838679 |
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author | Huang, Huei-Chung Wu, Yilin Yang, Qihang Qin, Li-Xuan |
author_facet | Huang, Huei-Chung Wu, Yilin Yang, Qihang Qin, Li-Xuan |
author_sort | Huang, Huei-Chung |
collection | PubMed |
description | We present a new R package PRECISION.array for assessing the performance of data normalization methods in connection with methods for sample classification. It includes two microRNA microarray datasets for the same set of tumor samples: a re-sampling-based algorithm for simulating additional paired datasets under various designs of sample-to-array assignment and levels of signal-to-noise ratios and a collection of numerical and graphical tools for method performance assessment. The package allows users to specify their own methods for normalization and classification, in addition to implementing three methods for training data normalization, seven methods for test data normalization, seven methods for classifier training, and two methods for classifier validation. It enables an objective and systemic evaluation of the operating characteristics of normalization and classification methods in microRNA microarrays. To our knowledge, this is the first such tool available. The R package can be downloaded freely at https://github.com/LXQin/PRECISION.array. |
format | Online Article Text |
id | pubmed-9354575 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-93545752022-08-06 PRECISION.array: An R Package for Benchmarking microRNA Array Data Normalization in the Context of Sample Classification Huang, Huei-Chung Wu, Yilin Yang, Qihang Qin, Li-Xuan Front Genet Genetics We present a new R package PRECISION.array for assessing the performance of data normalization methods in connection with methods for sample classification. It includes two microRNA microarray datasets for the same set of tumor samples: a re-sampling-based algorithm for simulating additional paired datasets under various designs of sample-to-array assignment and levels of signal-to-noise ratios and a collection of numerical and graphical tools for method performance assessment. The package allows users to specify their own methods for normalization and classification, in addition to implementing three methods for training data normalization, seven methods for test data normalization, seven methods for classifier training, and two methods for classifier validation. It enables an objective and systemic evaluation of the operating characteristics of normalization and classification methods in microRNA microarrays. To our knowledge, this is the first such tool available. The R package can be downloaded freely at https://github.com/LXQin/PRECISION.array. Frontiers Media S.A. 2022-07-22 /pmc/articles/PMC9354575/ /pubmed/35938023 http://dx.doi.org/10.3389/fgene.2022.838679 Text en Copyright © 2022 Huang, Wu, Yang and Qin. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Genetics Huang, Huei-Chung Wu, Yilin Yang, Qihang Qin, Li-Xuan PRECISION.array: An R Package for Benchmarking microRNA Array Data Normalization in the Context of Sample Classification |
title |
PRECISION.array: An R Package for Benchmarking microRNA Array Data Normalization in the Context of Sample Classification |
title_full |
PRECISION.array: An R Package for Benchmarking microRNA Array Data Normalization in the Context of Sample Classification |
title_fullStr |
PRECISION.array: An R Package for Benchmarking microRNA Array Data Normalization in the Context of Sample Classification |
title_full_unstemmed |
PRECISION.array: An R Package for Benchmarking microRNA Array Data Normalization in the Context of Sample Classification |
title_short |
PRECISION.array: An R Package for Benchmarking microRNA Array Data Normalization in the Context of Sample Classification |
title_sort | precision.array: an r package for benchmarking microrna array data normalization in the context of sample classification |
topic | Genetics |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9354575/ https://www.ncbi.nlm.nih.gov/pubmed/35938023 http://dx.doi.org/10.3389/fgene.2022.838679 |
work_keys_str_mv | AT huanghueichung precisionarrayanrpackageforbenchmarkingmicrornaarraydatanormalizationinthecontextofsampleclassification AT wuyilin precisionarrayanrpackageforbenchmarkingmicrornaarraydatanormalizationinthecontextofsampleclassification AT yangqihang precisionarrayanrpackageforbenchmarkingmicrornaarraydatanormalizationinthecontextofsampleclassification AT qinlixuan precisionarrayanrpackageforbenchmarkingmicrornaarraydatanormalizationinthecontextofsampleclassification |