2017
DOI: 10.1101/gr.216721.116
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Co-expression networks reveal the tissue-specific regulation of transcription and splicing

Abstract: Gene co-expression networks capture biologically important patterns in gene expression data, enabling functional analyses of genes, discovery of biomarkers, and interpretation of genetic variants. Most network analyses to date have been limited to assessing correlation between total gene expression levels in a single tissue or small sets of tissues. Here, we built networks that additionally capture the regulation of relative isoform abundance and splicing, along with tissue-specific connections unique to each … Show more

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Cited by 149 publications
(149 citation statements)
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“…Additional papers from the GTEx consortium for the v6p data describe the impact of rare genetic variation on gene expression 62 , methods for analysis of transcriptome data 27 , the discovery and characterization of regulatory networks across tissues 63 , and analyses of diverse regulatory processes such as RNA editing 64 and X-inactivation 65 . To enable ongoing use of the GTEx data, summary-level expression data and eQTLs across all tissues are available from the GTEx Portal (www.gtexportal.org), while all individual-level raw data have been deposited in dbGaP (accession phs000424.v6.p1).…”
Section: Discussionmentioning
confidence: 99%
“…Additional papers from the GTEx consortium for the v6p data describe the impact of rare genetic variation on gene expression 62 , methods for analysis of transcriptome data 27 , the discovery and characterization of regulatory networks across tissues 63 , and analyses of diverse regulatory processes such as RNA editing 64 and X-inactivation 65 . To enable ongoing use of the GTEx data, summary-level expression data and eQTLs across all tissues are available from the GTEx Portal (www.gtexportal.org), while all individual-level raw data have been deposited in dbGaP (accession phs000424.v6.p1).…”
Section: Discussionmentioning
confidence: 99%
“…RNA sequencing has enabled genome-wide transcriptome profiling at an unprecedented level of precision, [8][9][10][11] and is being increasingly applied to clinical investigation, including kidney allograft pathologies. [12][13][14] Recent advances in computational methods have enabled the extraction of additional genomic information from the RNA sequence data.…”
mentioning
confidence: 99%
“…assessing splicing events between sexes, within treatments), and (2) how do males and females differ in their response to stress (i.e., assessing splicing events within the sexes, between treatments). We did not include analyses between different tissues (e.g., male gonads to female gonads, or male pituitary to male hypothalamus) as numerous other studies have identified tissue-specific splicing events; these comparisons would not aid in discerning unique splicing patterns between sexes, or between treatments (Grosso et al, 2008;Saha et al, 2017;Pineda & Bradley, 2018). Whippet identifies splicing events by type, including Core Exon (CE), Alternate Acceptor (AA), Alternate Donor (AD), Retained Intron (RI), Tandem Alternative Polyadenylation Site (TE), Tandem Transcription Start Site (TS), Alternative First Exon (AF), and Alternative Last Exon (AL).…”
Section: Splicing Event Comparisonsmentioning
confidence: 99%