Analyzing Gene Expression Data from Microarray and Next‐Generation DNA Sequencing Transcriptome Profiling Assays Using GeneSifter Analysis Edition
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- Abstract
- Table of Contents
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Abstract
Transcription profiling with microarrays has become a standard procedure for comparing the levels of gene expression between pairs of samples, or multiple samples following different experimental treatments. New technologies, collectively known as next?generation DNA sequencing methods, are also starting to be used for transcriptome analysis. These technologies, with their low background, large capacity for data collection, and dynamic range, provide a powerful and complementary tool to the assays that formerly relied on microarrays. In this chapter, we describe two protocols for working with microarray data from pairs of samples and samples treated with multiple conditions, and discuss alternative protocols for carrying out similar analyses with next?generation DNA sequencing data from two different instrument platforms (Illumina GA and Applied Biosystems SOLiD). Curr. Protoc. Bioinform. 27:7.14.1?7.14.35. © 2009 by John Wiley & Sons, Inc.
Keywords: gene expression; microarray; RNA?Seq; transcriptome; GeneSifter Analysis Edition; next?generation DNA sequencing
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- Introduction
- Basic Protocol 1: Comparing Gene Expression from Paired Sample Data Obtained from Microarray Experiments
- Alternate Protocol 1: Compare Gene Expression from Paired Samples Obtained from Transcriptome Profiling Assays by Next‐Generation DNA Sequencing
- Basic Protocol 2: Comparing Gene Expression from Microarray Experiments with Multiple Conditions
- Alternate Protocol 2: Compare Gene Expression from Next‐Generation DNA Sequencing Data Obtained from Multiple Conditions
- Literature Cited
- Figures
- Tables
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Figure 7.14.1 Overview of the process for a pairwise comparison. View Image -
Figure 7.14.2 Setting up a pairwise comparison. View Image -
Figure 7.14.3 Analyzing the results from a pairwise comparison. View Image -
Figure 7.14.4 Scatter plot. View Image -
Figure 7.14.5 KEGG pathway results. View Image -
Figure 7.14.6 Gene ontology reports. View Image -
Figure 7.14.7 Analysis results from NGS data, obtained from an ABI SOLiD instrument. View Image -
Figure 7.14.8 Gene summaries for microarray and NGS data. A gene summary from a microarray sample is shown in the top half of the image and a summary for a sample analyzed by NGS is shown in the bottom half. Note the difference between the intensity and quality values. View Image -
Figure 7.14.9 Overview of an experiment comparing multiple conditions. View Image -
Figure 7.14.10 Box plot. View Image -
Figure 7.14.11 Box plots from a multiple‐condition experiment. (A ) Box plots from the six conditions that were compared in . Each plot represents the averaged data from the four to five replicates from each treatment. (B ) Box plots from biological replicates. Replicates from the AIN‐76, 0 lead samples are shown. View Image -
Figure 7.14.12 Analyzing the results from comparing multiple samples. View Image -
Figure 7.14.13 Gene‐specific navigation. View Image -
Figure 7.14.14 Illumina data. View Image -
Figure 7.14.15 Partitioning and silhouette data from a Next Gen experiment. View Image
Videos
Literature Cited
| Barrett, T., Troup, D.B., Wilhite, S.E., Ledoux, P., Rudnev, D., Evangelista, C., Kim, I.F., Soboleva, A., Tomashevsky, M., Marshall, K.A., Phillippy, K.H., Sherman, P.M., Muertter, R.N., and Edgar, R. 2009. NCBI GEO: Archive for high‐throughput functional genomic data. Nucleic Acids Res. 37:D885‐D890. | |
| Kaufman, L. and Rousseeuw, P. 1990. Finding Groups in Data: An Introduction to Cluster Analysis. Wiley Series in Probability and Statistics. John Wiley & Sons, Inc., New York. | |
| Kozul, C.D., Nomikos, A.P., Hampton, T.H., Warnke, L.A., Gosse, J.A., Davey, J.C., Thorpe, J.E., Jackson, B.P., Ihnat, M.A., and Hamilton, J.W. 2008. Laboratory diet profoundly alters gene expression and confounds genomic analysis in mouse liver and lung. Chem. Biol. Interact. 173:129‐140. | |
| Li, H. and Durbin, R. 2009. Fast and accurate short read alignment with Burrows‐Wheeler transform. Bioinformatics E‐pub May 18. | |
| Marioni, J.C., Mason, C.E., Mane, S.M., Stephens, M., and Gilad, Y. 2008. RNA‐seq: An assessment of technical reproducibility and comparison with gene expression arrays. Genome Res. 18:1509‐1517. | |
| Millenaar, F.F., Okyere, J., May, S.T., van Zanten, M., Voesenek, L.A., and Peeters, A.J. 2006. How to decide? Different methods of calculating gene expression from short oligonucleotide array data will give different results. BMC Bioinformatics 7:137. | |
| Mortazavi, A., Williams, B.A., McCue, K., Schaeffer, L., and Wold, B. 2008. Mapping and quantifying mammalian transcriptomes by RNA‐Seq. Nat. Methods 5:621‐628. | |
| Tang, F., Barbacioru, C., Wang, Y., Nordman, E., Lee, C., Xu, N., Wang, X., Bodeau, J., Tuch, B.B., Siddiqui, A., Lao, K., and Surani, M.A. 2009. mRNA‐Seq whole‐transcriptome analysis of a single cell. Nat. Methods 5:377‐382. | |
| Wang, Z., Gerstein, M., and Snyder, M. 2009. RNA‐Seq: A revolutionary tool for transcriptomics. Nat. Rev. Genet. 10:57‐63. | |
| Wheeler, D.L., Barrett, T., Benson, D.A., Bryant, S.H., Canese, K., Chetvernin, V., Church, D.M., Dicuccio, M., Edgar, R., Federhen, S., Feolo, M., Geer, L.Y., Helmberg, W., Kapustin, Y., Khovayko, O., Landsman, D., Lipman, D.J., Madden, T.L., Maglott, D.R., Miller, V., Ostell, J., Pruitt, K.D., Schuler, G.D., Shumway, M., Sequeira, E., Sherry, S.T., Sirotkin, K., Souvorov, A., Starchenko, G., Tatusov, R.L., Tatusova, T.A., Wagner, L., and Yaschenko, E. 2008. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 36:D13‐D21. | |
| Internet Resources | |
| http://www.geospiza.com/Support/datacenter.shtml | |
| The microarray data center at Geospiza, Inc. A diverse set of microarray data sets and tutorials on using GSAE are available from this page. | |
| http://www.ncbi.nlm.nih.gov/geo/ | |
| The NCBI GEO (Gene Expression Omnibus) database. GEO is a convenient place to find both microarray and Next Gen transcriptome datasets. | |
| http://www.ebi.ac.uk/microarray/ | |
| The ArrayExpress database from the European Bioinformatics Institute. Both microarray and Next Gen transcriptome data can be obtained here. | |
| http://www.ncbi.nlm.nih.gov/sra/ | |
| The NCBI SRA (Short Read Archive) database. Some Next Gen transcriptome data can be obtained here. |
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