2bd5a55547bf3e1c1b95622b6bb7dcd7cb4d2369
max
  Wed Oct 13 07:31:15 2021 -0700
finishing up gtex rna-seq coverage track, refs #27964

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+<H2>Description</H2>
+<P>
+The
+<a target="_blank" href="https://commonfund.nih.gov/GTEx/index">
+NIH Genotype-Tissue Expression (GTEx) project</a>
+determined genetic variation and gene expression in 52 tissues and 2 cell lines
+using RNA-seq data (V8, August 2019), on 17,382 samples from 948 adults.
+This track focuses on the gene expression part. It shows read coverage, from one
+single sample per tissue, selected for high-quality and high read depth.
+The data is summarized to one number per base pair, the number of sequencing
+reads that cover this position. The plot allows finding out if a given exon is
+transcribed primarily in certain tissues and also whether transcription is
+uniform over the length of a single exon.
+</P>
+
+<H2>Display Conventions</H2>
+<P>
+This track follows the display conventions for composite 
+&quot;wiggle&quot; tracks. The subtracks, one per tissue, of this track 
+may be configured in a variety of ways to highlight different aspects of the 
+displayed data. The graphical configuration options are shown at the top of 
+the track description page, followed by a list of subtracks.  To display only 
+selected subtracks, uncheck the boxes next to the tracks you wish to hide. 
+For more information about the graphical configuration options, click the 
+<A HREF="../goldenPath/help/hgWiggleTrackHelp.html" TARGET=_blank>Graph
+configuration help</A> link.</P>
+Tissue colors were assigned to conform to the GTEx Consortium publication conventions.
+</P>
+
+In Dense mode, the darkness of the grayscale rectangle displayed for the gene reflects the absolute
+read count.
+</p>
+
+<H2>Methods</H2>
+<p>For background information about GTEx sample selection, see our 
+<a href="hgGtexTrackSettings?g=gtexGeneV8" target=_blank>GTEx gene expression
+track</a>. In short, samples were sequenced with the Illumina TrueSeq protocol
+on unstranded polyA+ librarires to obtain 76-bp paired end reads with
+HiSeq 2000 and 2500 machines.</p>
+
+<p>
+Sequence reads were aligned to the hg38/GRCh38 human genome using STAR v2.5.3a
+and the GENCODE 26 transcriptome. 
+The alignment pipeline is available
+<a target="_blank" href="https://github.com/broadinstitute/gtex-pipeline/tree/master/rnaseq">here</a>.
+For further method details, see the 
+<a target="_blank" href="https://gtexportal.org/home/documentationPage#staticTexAnalysisMethods">
+GTEx Portal Documentation</a> page.
+</p>
+
+<P>
+To obtain read coverage, the GTEx Laboratory, Data Analysis and Coordinating
+Center (LDACC) at the Broad Institute decided to select a single, high-quality
+representative sample for each tissue type, since aggregated tracks may
+obscure certain features or even introduce some artifacts (e.g. intronic
+coverage). For each tissue, the selected sample has the highest RIN value with
+a high coverage (&gt;80M reads) and exonic rate (&gt;85%). 
+The alignment-to-coverage pipeline is available from Github:
+<a target="_blank" href="https://github.com/broadinstitute/gtex-pipeline/blob/master/rnaseq/src/bam2coverage.py">Python script</a>,
+<a target="_blank" href="https://github.com/broadinstitute/gtex-pipeline/blob/master/rnaseq/Dockerfile">Docker file</a> and 
+<a target="_blank" href="https://github.com/broadinstitute/gtex-pipeline/blob/master/rnaseq/bam2coverage.wdl">Pipeline WDL description</a>. 
+</p>
+<p>To show the exact GTEx sample that was used for each tissue,
+click the "Schema" link on the track configuration page (above), the filename
+under "bigDataUrl" includes the identifier.</p>
+
+<H2>Subject and Sample Characteristics</H2>
+<P>
+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. 
+Summary plots of GTEx sample characteristics are available at the 
+<a target="_blank" href="https://gtexportal.org/home/tissueSummaryPage">
+GTEx Portal Tissue Summary</a> page.</p>
+
+<h2>Data Access</h2>
+<p>
+The raw data for the GTEx Read Coverage track can be accessed interactively through the 
+<a href="hgTables?db=$db&hgta_track=$db&hgta_group=allTables&hgta_table=gtexCov">
+</p>
+</p>
+For automated analysis and downloads, the track data files can be downloaded from 
+<a href="https://hgdownload.soe.ucsc.edu/gbdb/$db/gtex/cov/">our downloads server</a>
+or <a href="../goldenPath/help/api.html">the JSON API</a>.
+Individual regions or the whole genome annotation can be accessed as text using our utility
+<code>bigBedToBed</code>. Instructions for downloading the utility can be found 
+<a href="http://hgdownload.soe.ucsc.edu/downloads.html#utilities_downloads">here</a>. 
+That utility can also be used to obtain features within a given range, e.g. 
+<code>bigBedToBed http://hgdownload.soe.ucsc.edu/gbdb/hg38/gtex/gtexGeneV8.bb -chrom=chr21
+-start=0 -end=100000000 stdout</code></p>
+<p>
+Data can also be obtained directly from GTEx at the following link:
+<a href="https://gtexportal.org/home/datasets" target=_blank>
+https://gtexportal.org/home/datasets</a></p>
+
+<H2>Credits</H2>
+<P>
+Statistical analysis and data interpretation was performed by The GTEx Consortium Analysis 
+Working Group. 
+Data was provided by the GTEx LDACC at The Broad Institute of MIT and Harvard.</P>
+
+<H2>References</H2>
+<p>
+GTEx Consortium. 
+<a href="https://www.researchgate.net/publication/336246636_The_GTEx_Consortium_atlas_of_genetic_regulatory_effects_across_human_tissues" target="_blank">
+The GTEx Consortium atlas of genetic regulatory effects across human tissues.</a>
+<em>In press.</em></p>
+
+<p>
+GTEx Consortium.
+<a href="https://www.nature.com/ng/journal/v45/n6/full/ng.2653.html" target="_blank">
+The Genotype-Tissue Expression (GTEx) project</a>.
+<em>Nat Genet</em>. 2013 Jun;45(6):580-5.
+PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/23715323" target="_blank">23715323</a>; 
+PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4010069/" target="_blank">PMC4010069</a> </p>
+
+<p>
+Carithers LJ, Ardlie K, Barcus M, Branton PA, Britton A, Buia SA, Compton CC, DeLuca DS, 
+Peter-Demchok J, Gelfand ET <em>et al</em>.
+<a href="https://www.ncbi.nlm.nih.gov/pmc/articles/pmid/26484571/" target="_blank">
+A Novel Approach to High-Quality Postmortem Tissue Procurement: The GTEx Project</a>.
+<em>Biopreserv Biobank</em>. 2015 Oct;13(5):311-9.
+PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/26484571" target="_blank">26484571</a>; 
+PMC: <a href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4675181/" target="_blank">PMC4675181</a></p>
+
+Mel&#233; M, Ferreira PG, Reverter F, DeLuca DS, Monlong J, Sammeth M, Young TR, Goldmann JM,
+Pervouchine DD, Sullivan TJ <em>et al</em>.
+<a href="https://science.sciencemag.org/content/348/6235/660" target="_blank">
+Human genomics. The human transcriptome across tissues and individuals</a>.
+<em>Science</em>. 2015 May 8;348(6235):660-5.
+PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/25954002" target="_blank">25954002</a>; PMC: <a
+href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC4547472/" target="_blank">PMC4547472</a></p>
+
+<p>
+DeLuca DS, Levin JZ, Sivachenko A, Fennell T, Nazaire MD, Williams C, Reich M, Winckler W, Getz G.
+<a href="https://academic.oup.com/bioinformatics/article-lookup/doi/10.1093/bioinformatics/bts196"
+target="_blank">
+RNA-SeQC: RNA-seq metrics for quality control and process optimization</a>.
+<em>Bioinformatics</em>. 2012 Jun 1;28(11):1530-2.
+PMID: <a href="https://www.ncbi.nlm.nih.gov/pubmed/22539670" target="_blank">22539670</a>; PMC: <a
+href="https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3356847/" target="_blank">PMC3356847</a></p>
+