Cargando…

Application of microarray outlier detection methodology to psychiatric research

BACKGROUND: Most microarray data processing methods negate extreme expression values or alter them so that they do not lie outside the mean level of variation of the system. While microarrays generate a substantial amount of false positive and spurious results, some of the extreme expression values...

Descripción completa

Detalles Bibliográficos
Autores principales: Ernst, Carl, Bureau, Alexandre, Turecki, Gustavo
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2008
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2364617/
https://www.ncbi.nlm.nih.gov/pubmed/18433482
http://dx.doi.org/10.1186/1471-244X-8-29
_version_ 1782153994413539328
author Ernst, Carl
Bureau, Alexandre
Turecki, Gustavo
author_facet Ernst, Carl
Bureau, Alexandre
Turecki, Gustavo
author_sort Ernst, Carl
collection PubMed
description BACKGROUND: Most microarray data processing methods negate extreme expression values or alter them so that they do not lie outside the mean level of variation of the system. While microarrays generate a substantial amount of false positive and spurious results, some of the extreme expression values may be valid and could represent true biological findings. METHODS: We propose a simple method to screen brain microarray data to detect individual differences across a psychiatric sample set. We demonstrate in two different samples how this method can be applied. RESULTS: This method targets high-throughput technology to psychiatric research on a subject-specific basis. CONCLUSION: Assessing microarray data for both mean group effects and individual effects can lead to more robust findings in psychiatric genetics.
format Text
id pubmed-2364617
institution National Center for Biotechnology Information
language English
publishDate 2008
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-23646172008-05-02 Application of microarray outlier detection methodology to psychiatric research Ernst, Carl Bureau, Alexandre Turecki, Gustavo BMC Psychiatry Technical Advance BACKGROUND: Most microarray data processing methods negate extreme expression values or alter them so that they do not lie outside the mean level of variation of the system. While microarrays generate a substantial amount of false positive and spurious results, some of the extreme expression values may be valid and could represent true biological findings. METHODS: We propose a simple method to screen brain microarray data to detect individual differences across a psychiatric sample set. We demonstrate in two different samples how this method can be applied. RESULTS: This method targets high-throughput technology to psychiatric research on a subject-specific basis. CONCLUSION: Assessing microarray data for both mean group effects and individual effects can lead to more robust findings in psychiatric genetics. BioMed Central 2008-04-23 /pmc/articles/PMC2364617/ /pubmed/18433482 http://dx.doi.org/10.1186/1471-244X-8-29 Text en Copyright © 2008 Ernst 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 Technical Advance
Ernst, Carl
Bureau, Alexandre
Turecki, Gustavo
Application of microarray outlier detection methodology to psychiatric research
title Application of microarray outlier detection methodology to psychiatric research
title_full Application of microarray outlier detection methodology to psychiatric research
title_fullStr Application of microarray outlier detection methodology to psychiatric research
title_full_unstemmed Application of microarray outlier detection methodology to psychiatric research
title_short Application of microarray outlier detection methodology to psychiatric research
title_sort application of microarray outlier detection methodology to psychiatric research
topic Technical Advance
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC2364617/
https://www.ncbi.nlm.nih.gov/pubmed/18433482
http://dx.doi.org/10.1186/1471-244X-8-29
work_keys_str_mv AT ernstcarl applicationofmicroarrayoutlierdetectionmethodologytopsychiatricresearch
AT bureaualexandre applicationofmicroarrayoutlierdetectionmethodologytopsychiatricresearch
AT tureckigustavo applicationofmicroarrayoutlierdetectionmethodologytopsychiatricresearch