The NIH Genotype-Tissue Expression (GTEx) project was created to establish a sample and data resource for studies on the relationship between genetic variation and gene expression in multiple human tissues. This track shows the median transcript expression levels in 53 tissues, based on RNA-seq data from the GTEx midpoint milestone data release (V6, October 2015). This track is based on the kallisto recompute of the GTEx data using the toil pipeline.
In Full and Pack display modes, expression for each transcript is represented by a colored bargraph,
where the height of each bar represents the median expression level across all samples for a
tissue, and the bar color indicates the tissue.
The bargraph display has the same width and tissue order for all genes.
Mouse hover over a bar will show the tissue and median expression level.
The Squish display mode draws a rectangle for each gene, colored to indicate the tissue
with highest expression level if it contributes more than 10% to the overall expression
(and colored black if no tissue predominates).
In Dense mode, the darkness of the grayscale rectangle displayed for the gene reflects the total
median expression level across all tissues.
Click-through on a graph displays a boxplot of expression level quartiles with outliers, per tissue, along with a link to the corresponding gene page on the GTEx Portal.
The track configuration page provides controls to limit the genes and tissues displayed, and to select raw or log transformed expression level display.RNA-seq was performed by the GTEx Laboratory, Data Analysis and Coordinating Center (LDACC) at the Broad Institute. The Illumina TruSeq protocol was used to create an unstranded polyA+ library sequenced on the Illumina HiSeq 2000 platform to produce 76-bp paired end reads at a depth averaging 50M aligned reads per sample.
Sequence reads for this track were quantified to the hg38/GRCh38 human genome using kallisto assisted by the GENCODE v23 transcriptome definition. Read quantification was performed at UCSC by the Computational Genomics lab, using the Toil pipeline. The resulting kallisto files were combined to generate a transcript per million (tpm) expression matrix using the UCSC tool kallistoToMatrix. Average tpm expression values for each tissue were calculated and used to generate a bed6+5 file that is the base of the track. This was done using the UCSC tool expMatrixToBarchartBed. The bed track was then converted to a bigBed file using the UCSC tool bedToBigBed.
The scientific goal of the GTEx project required that the donors and their biospecimen present with no evidence of disease. The tissue types collected were chosen based on their clinical significance, logistical feasibility and their relevance to the scientific goal of the project and the research community. Postmortem samples were collected from non-diseased donors with ages ranging from 20 to 79. 34.4% of donors were female and 65.6% male.
Additional summary plots of GTEx sample characteristics are available at the GTEx Portal Tissue Summary page.
J. Vivian et al., Rapid and efficient analysis of 20,000 RNA-seq samples with Toil bioRxiv bioRxiv, vol. 2, p. 62497, 2016.
GTEx Consortium. The Genotype-Tissue Expression (GTEx) project. Nat Genet. 2013 Jun;45(6):580-5. PMID: 23715323; PMC: PMC4010069Carithers LJ, Ardlie K, Barcus M, Branton PA, Britton A, Buia SA, Compton CC, DeLuca DS, Peter-Demchok J, Gelfand ET et al. A Novel Approach to High-Quality Postmortem Tissue Procurement: The GTEx Project. Biopreserv Biobank. 2015 Oct;13(5):311-9. PMID: 26484571; PMC: PMC4675181
Melé M, Ferreira PG, Reverter F, DeLuca DS, Monlong J, Sammeth M, Young TR, Goldmann JM, Pervouchine DD, Sullivan TJ et al. Human genomics. The human transcriptome across tissues and individuals. Science. 2015 May 8;348(6235):660-5. PMID: 25954002; PMC: PMC4547472
DeLuca DS, Levin JZ, Sivachenko A, Fennell T, Nazaire MD, Williams C, Reich M, Winckler W, Getz G. RNA-SeQC: RNA-seq metrics for quality control and process optimization. Bioinformatics. 2012 Jun 1;28(11):1530-2. PMID: 22539670; PMC: PMC3356847