Cargando…

Difference-based clustering of short time-course microarray data with replicates

BACKGROUND: There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain knowledge and do not incorporate information from replicates. Moreover, the results are not always easy to interpret biologic...

Descripción completa

Detalles Bibliográficos
Autores principales: Kim, Jihoon, Kim, Ju Han
Formato: Texto
Lenguaje:English
Publicado: BioMed Central 2007
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1952071/
https://www.ncbi.nlm.nih.gov/pubmed/17629922
http://dx.doi.org/10.1186/1471-2105-8-253
_version_ 1782134591437406208
author Kim, Jihoon
Kim, Ju Han
author_facet Kim, Jihoon
Kim, Ju Han
author_sort Kim, Jihoon
collection PubMed
description BACKGROUND: There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain knowledge and do not incorporate information from replicates. Moreover, the results are not always easy to interpret biologically. RESULTS: We propose a novel algorithm for identifying a subset of genes sharing a significant temporal expression pattern when replicates are used. Our algorithm requires no prior knowledge, instead relying on an observed statistic which is based on the first and second order differences between adjacent time-points. Here, a pattern is predefined as the sequence of symbols indicating direction and the rate of change between time-points, and each gene is assigned to a cluster whose members share a similar pattern. We evaluated the performance of our algorithm to those of K-means, Self-Organizing Map and the Short Time-series Expression Miner methods. CONCLUSIONS: Assessments using simulated and real data show that our method outperformed aforementioned algorithms. Our approach is an appropriate solution for clustering short time-course microarray data with replicates.
format Text
id pubmed-1952071
institution National Center for Biotechnology Information
language English
publishDate 2007
publisher BioMed Central
record_format MEDLINE/PubMed
spelling pubmed-19520712007-08-25 Difference-based clustering of short time-course microarray data with replicates Kim, Jihoon Kim, Ju Han BMC Bioinformatics Methodology Article BACKGROUND: There are some limitations associated with conventional clustering methods for short time-course gene expression data. The current algorithms require prior domain knowledge and do not incorporate information from replicates. Moreover, the results are not always easy to interpret biologically. RESULTS: We propose a novel algorithm for identifying a subset of genes sharing a significant temporal expression pattern when replicates are used. Our algorithm requires no prior knowledge, instead relying on an observed statistic which is based on the first and second order differences between adjacent time-points. Here, a pattern is predefined as the sequence of symbols indicating direction and the rate of change between time-points, and each gene is assigned to a cluster whose members share a similar pattern. We evaluated the performance of our algorithm to those of K-means, Self-Organizing Map and the Short Time-series Expression Miner methods. CONCLUSIONS: Assessments using simulated and real data show that our method outperformed aforementioned algorithms. Our approach is an appropriate solution for clustering short time-course microarray data with replicates. BioMed Central 2007-07-14 /pmc/articles/PMC1952071/ /pubmed/17629922 http://dx.doi.org/10.1186/1471-2105-8-253 Text en Copyright © 2007 Kim and Kim; 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 Methodology Article
Kim, Jihoon
Kim, Ju Han
Difference-based clustering of short time-course microarray data with replicates
title Difference-based clustering of short time-course microarray data with replicates
title_full Difference-based clustering of short time-course microarray data with replicates
title_fullStr Difference-based clustering of short time-course microarray data with replicates
title_full_unstemmed Difference-based clustering of short time-course microarray data with replicates
title_short Difference-based clustering of short time-course microarray data with replicates
title_sort difference-based clustering of short time-course microarray data with replicates
topic Methodology Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC1952071/
https://www.ncbi.nlm.nih.gov/pubmed/17629922
http://dx.doi.org/10.1186/1471-2105-8-253
work_keys_str_mv AT kimjihoon differencebasedclusteringofshorttimecoursemicroarraydatawithreplicates
AT kimjuhan differencebasedclusteringofshorttimecoursemicroarraydatawithreplicates