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Comparison of Two Methods for Detecting Alternative Splice Variants Using GeneChip(®) Exon Arrays

The Affymetrix GeneChip Exon Array can be used to detect alternative splice variants. Microarray Detection of Alternative Splicing (MIDAS) and Partek(®) Genomics Suite (Partek(®) GS) are among the most popular analytical methods used to analyze exon array data. While both methods utilize statistical...

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Autores principales: Fan, Wenhong, Stirewalt, Derek L., Radich, Jerald P., Zhao, Lueping
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Master Publishing Group 2011
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3614835/
https://www.ncbi.nlm.nih.gov/pubmed/23675234
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author Fan, Wenhong
Stirewalt, Derek L.
Radich, Jerald P.
Zhao, Lueping
author_facet Fan, Wenhong
Stirewalt, Derek L.
Radich, Jerald P.
Zhao, Lueping
author_sort Fan, Wenhong
collection PubMed
description The Affymetrix GeneChip Exon Array can be used to detect alternative splice variants. Microarray Detection of Alternative Splicing (MIDAS) and Partek(®) Genomics Suite (Partek(®) GS) are among the most popular analytical methods used to analyze exon array data. While both methods utilize statistical significance for testing, MIDAS and Partek(®) GS could produce somewhat different results due to different underlying assumptions. Comparing MIDAS and Partek(®) GS is quite difficult due to their substantially different mathematical formulations and assumptions regarding alternative splice variants. For meaningful comparison, we have used the previously published generalized probe model (GPM) which encompasses both MIDAS and Partek(®) GS under different assumptions. We analyzed a colon cancer exon array data set using MIDAS, Partek(®) GS and GPM. MIDAS and Partek(®) GS produced quite different sets of genes that are considered to have alternative splice variants. Further, we found that GPM produced results similar to MIDAS as well as to Partek(®) GS under their respective assumptions. Within the GPM, we show how discoveries relating to alternative variants can be quite different due to different assumptions. MIDAS focuses on relative changes in expression values across different exons within genes and tends to be robust but less efficient. Partek(®) GS, however, uses absolute expression values of individual exons within genes and tends to be more efficient but more sensitive to the presence of outliers. From our observations, we conclude that MIDAS and Partek(®) GS produce complementary results, and discoveries from both analyses should be considered.
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spelling pubmed-36148352013-05-01 Comparison of Two Methods for Detecting Alternative Splice Variants Using GeneChip(®) Exon Arrays Fan, Wenhong Stirewalt, Derek L. Radich, Jerald P. Zhao, Lueping Int J Biomed Sci Article The Affymetrix GeneChip Exon Array can be used to detect alternative splice variants. Microarray Detection of Alternative Splicing (MIDAS) and Partek(®) Genomics Suite (Partek(®) GS) are among the most popular analytical methods used to analyze exon array data. While both methods utilize statistical significance for testing, MIDAS and Partek(®) GS could produce somewhat different results due to different underlying assumptions. Comparing MIDAS and Partek(®) GS is quite difficult due to their substantially different mathematical formulations and assumptions regarding alternative splice variants. For meaningful comparison, we have used the previously published generalized probe model (GPM) which encompasses both MIDAS and Partek(®) GS under different assumptions. We analyzed a colon cancer exon array data set using MIDAS, Partek(®) GS and GPM. MIDAS and Partek(®) GS produced quite different sets of genes that are considered to have alternative splice variants. Further, we found that GPM produced results similar to MIDAS as well as to Partek(®) GS under their respective assumptions. Within the GPM, we show how discoveries relating to alternative variants can be quite different due to different assumptions. MIDAS focuses on relative changes in expression values across different exons within genes and tends to be robust but less efficient. Partek(®) GS, however, uses absolute expression values of individual exons within genes and tends to be more efficient but more sensitive to the presence of outliers. From our observations, we conclude that MIDAS and Partek(®) GS produce complementary results, and discoveries from both analyses should be considered. Master Publishing Group 2011-09 /pmc/articles/PMC3614835/ /pubmed/23675234 Text en © Wenhong Fan et al. Licensee Master Publishing Group http://creativecommons.org/licenses/by/2.5/ This is an open-access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/2.5/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Article
Fan, Wenhong
Stirewalt, Derek L.
Radich, Jerald P.
Zhao, Lueping
Comparison of Two Methods for Detecting Alternative Splice Variants Using GeneChip(®) Exon Arrays
title Comparison of Two Methods for Detecting Alternative Splice Variants Using GeneChip(®) Exon Arrays
title_full Comparison of Two Methods for Detecting Alternative Splice Variants Using GeneChip(®) Exon Arrays
title_fullStr Comparison of Two Methods for Detecting Alternative Splice Variants Using GeneChip(®) Exon Arrays
title_full_unstemmed Comparison of Two Methods for Detecting Alternative Splice Variants Using GeneChip(®) Exon Arrays
title_short Comparison of Two Methods for Detecting Alternative Splice Variants Using GeneChip(®) Exon Arrays
title_sort comparison of two methods for detecting alternative splice variants using genechip(®) exon arrays
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3614835/
https://www.ncbi.nlm.nih.gov/pubmed/23675234
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