Design and analysis of experiments with high throughput biological assay data

Research output: Contribution to journalArticle

55 Citations (Scopus)

Abstract

The design and analysis of experiments using gene expression microarrays is a topic of considerable current research, and work is beginning to appear on the analysis of proteomics and metabolomics data by mass spectrometry and NMR spectroscopy. The literature in this area is evolving rapidly, and commercial software for analysis of array or proteomics data is rarely up to date, and is essentially nonexistent for metabolomics data. In this paper, I review some of the issues that should concern any biologists planning to use such high-throughput biological assay data in an experimental investigation. Technical details are kept to a minimum, and may be found in the referenced literature, as well as in the many excellent papers which space limitations prevent my describing. There are usually a number of viable options for design and analysis of such experiments, but unfortunately, there are even more non-viable ones that have been used even in the published literature. This is an area in which up-to-date knowledge of the literature is indispensable for efficient and effective design and analysis of these experiments. In general, we concentrate on relatively simple analyses, often focusing on identifying differentially expressed genes and the comparable issues in mass spectrometry and NMR spectroscopy (consistent differences in peak heights or areas for example). Complex multivariate and pattern recognition methods also need much attention, but the issues we describe in this paper must be dealt with first. The literature on analysis of proteomics and metabolomics data is as yet sparse, so the main focus of this paper will be on methods devised for analysis of gene expression data that generalize to proteomics and metabolomics, with some specific comments near the end on analysis of metabolomics data by mass spectrometry and NMR spectroscopy.

Original languageEnglish (US)
Pages (from-to)703-713
Number of pages11
JournalSeminars in Cell and Developmental Biology
Volume15
Issue number6 SPEC. ISS.
DOIs
StatePublished - Dec 2004

Fingerprint

High-Throughput Screening Assays
Metabolomics
Mass Spectrometry
Proteomics
Magnetic Resonance Spectroscopy
Gene Expression
Software
Research
Genes

Keywords

  • Gene expression
  • Mass spectrometry
  • Metabolomics
  • Microarray
  • NMR spectroscopy

ASJC Scopus subject areas

  • Developmental Biology

Cite this

Design and analysis of experiments with high throughput biological assay data. / Rocke, David M.

In: Seminars in Cell and Developmental Biology, Vol. 15, No. 6 SPEC. ISS., 12.2004, p. 703-713.

Research output: Contribution to journalArticle

@article{c0909038bb3346508f5528993ff4b1ad,
title = "Design and analysis of experiments with high throughput biological assay data",
abstract = "The design and analysis of experiments using gene expression microarrays is a topic of considerable current research, and work is beginning to appear on the analysis of proteomics and metabolomics data by mass spectrometry and NMR spectroscopy. The literature in this area is evolving rapidly, and commercial software for analysis of array or proteomics data is rarely up to date, and is essentially nonexistent for metabolomics data. In this paper, I review some of the issues that should concern any biologists planning to use such high-throughput biological assay data in an experimental investigation. Technical details are kept to a minimum, and may be found in the referenced literature, as well as in the many excellent papers which space limitations prevent my describing. There are usually a number of viable options for design and analysis of such experiments, but unfortunately, there are even more non-viable ones that have been used even in the published literature. This is an area in which up-to-date knowledge of the literature is indispensable for efficient and effective design and analysis of these experiments. In general, we concentrate on relatively simple analyses, often focusing on identifying differentially expressed genes and the comparable issues in mass spectrometry and NMR spectroscopy (consistent differences in peak heights or areas for example). Complex multivariate and pattern recognition methods also need much attention, but the issues we describe in this paper must be dealt with first. The literature on analysis of proteomics and metabolomics data is as yet sparse, so the main focus of this paper will be on methods devised for analysis of gene expression data that generalize to proteomics and metabolomics, with some specific comments near the end on analysis of metabolomics data by mass spectrometry and NMR spectroscopy.",
keywords = "Gene expression, Mass spectrometry, Metabolomics, Microarray, NMR spectroscopy",
author = "Rocke, {David M}",
year = "2004",
month = "12",
doi = "10.1016/j.semcdb.2004.09.007",
language = "English (US)",
volume = "15",
pages = "703--713",
journal = "Seminars in Cell and Developmental Biology",
issn = "1084-9521",
publisher = "Academic Press Inc.",
number = "6 SPEC. ISS.",

}

TY - JOUR

T1 - Design and analysis of experiments with high throughput biological assay data

AU - Rocke, David M

PY - 2004/12

Y1 - 2004/12

N2 - The design and analysis of experiments using gene expression microarrays is a topic of considerable current research, and work is beginning to appear on the analysis of proteomics and metabolomics data by mass spectrometry and NMR spectroscopy. The literature in this area is evolving rapidly, and commercial software for analysis of array or proteomics data is rarely up to date, and is essentially nonexistent for metabolomics data. In this paper, I review some of the issues that should concern any biologists planning to use such high-throughput biological assay data in an experimental investigation. Technical details are kept to a minimum, and may be found in the referenced literature, as well as in the many excellent papers which space limitations prevent my describing. There are usually a number of viable options for design and analysis of such experiments, but unfortunately, there are even more non-viable ones that have been used even in the published literature. This is an area in which up-to-date knowledge of the literature is indispensable for efficient and effective design and analysis of these experiments. In general, we concentrate on relatively simple analyses, often focusing on identifying differentially expressed genes and the comparable issues in mass spectrometry and NMR spectroscopy (consistent differences in peak heights or areas for example). Complex multivariate and pattern recognition methods also need much attention, but the issues we describe in this paper must be dealt with first. The literature on analysis of proteomics and metabolomics data is as yet sparse, so the main focus of this paper will be on methods devised for analysis of gene expression data that generalize to proteomics and metabolomics, with some specific comments near the end on analysis of metabolomics data by mass spectrometry and NMR spectroscopy.

AB - The design and analysis of experiments using gene expression microarrays is a topic of considerable current research, and work is beginning to appear on the analysis of proteomics and metabolomics data by mass spectrometry and NMR spectroscopy. The literature in this area is evolving rapidly, and commercial software for analysis of array or proteomics data is rarely up to date, and is essentially nonexistent for metabolomics data. In this paper, I review some of the issues that should concern any biologists planning to use such high-throughput biological assay data in an experimental investigation. Technical details are kept to a minimum, and may be found in the referenced literature, as well as in the many excellent papers which space limitations prevent my describing. There are usually a number of viable options for design and analysis of such experiments, but unfortunately, there are even more non-viable ones that have been used even in the published literature. This is an area in which up-to-date knowledge of the literature is indispensable for efficient and effective design and analysis of these experiments. In general, we concentrate on relatively simple analyses, often focusing on identifying differentially expressed genes and the comparable issues in mass spectrometry and NMR spectroscopy (consistent differences in peak heights or areas for example). Complex multivariate and pattern recognition methods also need much attention, but the issues we describe in this paper must be dealt with first. The literature on analysis of proteomics and metabolomics data is as yet sparse, so the main focus of this paper will be on methods devised for analysis of gene expression data that generalize to proteomics and metabolomics, with some specific comments near the end on analysis of metabolomics data by mass spectrometry and NMR spectroscopy.

KW - Gene expression

KW - Mass spectrometry

KW - Metabolomics

KW - Microarray

KW - NMR spectroscopy

UR - http://www.scopus.com/inward/record.url?scp=9244226546&partnerID=8YFLogxK

UR - http://www.scopus.com/inward/citedby.url?scp=9244226546&partnerID=8YFLogxK

U2 - 10.1016/j.semcdb.2004.09.007

DO - 10.1016/j.semcdb.2004.09.007

M3 - Article

VL - 15

SP - 703

EP - 713

JO - Seminars in Cell and Developmental Biology

JF - Seminars in Cell and Developmental Biology

SN - 1084-9521

IS - 6 SPEC. ISS.

ER -