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Your Environment. Your Health.

Boston University: Dataset Details, ID=GSE118797

Superfund Research Program

The Long-term Impacts of Early Life Exposure to Superfund Chemicals in Humans and Wildlife

Center Director: David H. Sherr
Grant Number: P42ES007381
Funding Period: 1995-2020
View this project in the NIH Research Portfolio Online Reporting Tools (RePORT)

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Title: Assessment of a highly multiplexed RNA sequencing platform and comparison to existing high-throughput gene expression profiling techniques

Accession Number: GSE118797

Link to Dataset: https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE118797

Repository: Gene Expression Omnibus (GEO)

Data Type(s): Gene Expression

Experiment Type(s): Expression profiling by high throughput sequencing

Organism(s): Homo sapiens

Summary: In this study, we report the performance of one such technique denoted as sparse full length sequencing (SFL), a ribosomal RNA depletion-based RNA sequencing approach that allows for the simultaneous sequencing of 96 samples and higher. We offer comparisons to well established single-sample techniques, including: full coverage Poly-A capture RNA-seq and microarray, as well as another low-cost highly multiplexed technique known as 3' digital gene expression (3' DGE). Data was generated for a set of exposure experiments on immortalized human lung epithelial (AALE) cells in a two-by-two study design, in which samples received both genetic and chemical perturbations of known oncogenes/tumor suppressors and lung carcinogens. SFL demonstrated improved performance over 3' DGE in terms of coverage, power to detect differential gene expression, and biological recapitulation of patterns of differential gene expression from in vivo lung cancer mutation signatures.

Publication(s) associated with this dataset:
  • Reed E, Moses E, Xiao X, Liu G, Campbell J, Perdomo C, Monti S. 2019. Assessment of a highly multiplexed RNA sequencing platform and comparison to existing high-throughput gene expression profiling techniques. Front Genet 10:14. doi:10.3389/fgene.2019.00150 PMID:30891063 PMCID:PMC6411637
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