RNA-Seq and expression microarray highlight different aspects of the fetal amniotic fluid transcriptome [RNA-Seq]
Transcriptomics Dataset
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General Information
AccessionGSE49890
TitleRNA-Seq and expression microarray highlight different aspects of the fetal amniotic fluid transcriptome [RNA-Seq]
DescriptionThe second trimester fetal transcriptome can be assessed based on cell-free RNA found within the amniotic fluid supernatant. The objective of this study was to compare the suitability of two technologies for profiling the human fetal transcriptome: RNA-Seq and expression microarray. Comparisons were based on total numbers of gene detected, rank-order gene expression, and functional genomic analysis. Fewer gene transcripts were observed using RNA-Seq than microarray (4,158 vs 8,842). Correlation of total expression within each sample ranged from R=0.43 to R=0.57. On average, there was 59%% concordance in gene identity among the top 10%% of genes ranked by expression. The RNA-Seq data yielded more significant pathways enrichment within the ?Physiological Systems Development and Function? categories of IPA. Alternative splicing of many well-known genes, including those previously studied in fetal development, such as H19 and IGF2 is detected by RNA-Seq. Also included in this paper is discussion of the technical challenges inherent to working with cell-free fetal RNA and possible solutions.
Landing Pagehttps://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE49890
RepositoryGene Expression Omnibus
Tools used to analyze the dataset

Dataset Accession

ARCHS4
Published September 2017
ARCHS4 provides access to gene counts from HiSeq 2000 and HiSeq 2500 platforms for human and mouse experiments from GEO ...
4645
Clustergrammer
Published October 2017
Web-based tool for visualizing and analyzing high-dimensional data as interactive and shareable heatmaps
4645
Canned Analyses generated with the dataset

Dataset Accession
Tool Name

Interactive heatmap visualization of RNA-seq dataset GSE49890
Highly interactive web-based heatmap visualization of the top 500 most variable genes in t...
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