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Revisiting Global Gene Expression Analysis (RNA-Seq)

ABSTRACT: Gene expression analysis is a widely used and powerful method for investigating the transcriptional behavior of biological systems, for classifying cell states in disease and for many other purposes. Recent studies indicate that common assumptions currently embedded in experimental and analytical practices can lead to misinterpretation of global gene expression data. We discuss these assumptions and describe solutions that should minimize erroneous interpretation of gene expression data from multiple analysis platforms. Polyadenylated RNA depleted of ribosomal content was used for preparation of two independent sequencing libraries (low-Myc & high-Myc). A panel of synthetic RNA's was added to these populations, based on cell number.

ORGANISM(S): Homo sapiens

SUBMITTER: Richard Young

PROVIDER: E-GEOD-40783 | biostudies-arrayexpress |

REPOSITORIES: biostudies-arrayexpress

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Revisiting global gene expression analysis.

Lovén Jakob J Orlando David A DA Sigova Alla A AA Lin Charles Y CY Rahl Peter B PB Burge Christopher B CB Levens David L DL Lee Tong Ihn TI Young Richard A RA

Cell 20121001 3

Gene expression analysis is a widely used and powerful method for investigating the transcriptional behavior of biological systems, for classifying cell states in disease, and for many other purposes. Recent studies indicate that common assumptions currently embedded in experimental and analytical practices can lead to misinterpretation of global gene expression data. We discuss these assumptions and describe solutions that should minimize erroneous interpretation of gene expression data from mu ...[more]

PMID: 23101621

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Revisiting Global Gene Expression Analysis (Microarray)

Project description:Gene expression analysis is a widely used and powerful method for investigating the transcriptional behavior of biological systems, for classifying cell states in disease and for many other purposes. Recent studies indicate that common assumptions currently embedded in experimental and analytical practices can lead to misinterpretation of global gene expression data. We discuss these assumptions and describe solutions that should minimize erroneous interpretation of gene expression data from multiple analysis platforms. RNA was extracted from cells expressing low or high levels of c-Myc. A panel of synthetic RNA's was added to these populations, based on cell number. Total RNA was then extracted and processed on Affymetrix microarrays in biological duplicate.

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2015-02-01 | E-GEOD-59480 | biostudies-arrayexpress

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