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We thank C. Kingsford and D. Filippova for their assistance in adding SHARQ metadata to recount2. recount2 data are hosted on SciServer, a collaborative research environment for large-scale data-driven science. It is being developed at, and administered by, the Institute for Data Intensive Engineering and Science at Johns Hopkins University. SciServer is funded by the National Science Foundation Award ACI-1261715. For more information about SciServer, visit http://www.sciserver.org/. We thank E. Lehnert and P. Radovic at Seven Bridges for their help accessing RNA-seq data from TCGA using the Cancer Genomics Cloud API and depositing results in a shared bucket on Amazon S3. We also thank other Seven Bridges team members for facilitating our TCGA reanalysis, including B. Dusenbery, N. Tijanic, M. Kovacevic, M. Sadoff and G. Kaushik. The Genotype-Tissue Expression (GTEx) Project was supported by the Common Fund of the Office of the Director of the National Institutes of Health. Additional funds were provided by the NCI, NHGRI, NHLBI, NIDA, NIMH and NINDS. Donors were enrolled at Biospecimen Source Sites funded by NCI/SAIC-Frederick, Inc. (SAIC-F) subcontracts to the National Disease Research Interchange (10XS170), Roswell Park Cancer Institute (10XS171), and Science Care, Inc. (X10S172). The Laboratory, Data Analysis, and Coordinating Center (LDACC) was funded through a contract (HHSN268201000029C) to The Broad Institute, Inc. Biorepository operations were funded through an SAIC-F subcontract to Van Andel Institute (10ST1035). Additional data repository and project management were provided by SAIC-F (HHSN261200800001E). The Brain Bank was supported by a supplement to University of Miami grants DA006227 and DA033684 and to contract N01MH000028. Statistical Methods development grants were made to the University of Geneva (MH090941 & MH101814), the University of Chicago (MH090951, MH090937, MH101820, MH101825), the University of North Carolina–Chapel Hill (MH090936 & MH101819), Harvard University (MH090948), Stanford University (MH101782), Washington University St. Louis (MH101810) and the University of Pennsylvania (MH101822). The data used for the analyses described in this manuscript were obtained from: the GTEx Portal on 11/21/15 and/or dbGaP accession number phs000424.v6.p1 on 11/30/15—12/04/15. Funding: B.L., J.T.L., L.C.T., S.E., A.N., M.T., K.H. and K.K. were supported by NIH R01 GM105705. L.C.T. was supported by Consejo Nacional de Ciencia y Tecnología México 351535. L.C.T. and A.E.J. were supported by 1R21MH109956. Amazon Web Services experiments were supported by AWS in Education research grants. Storage costs on S3 for TCGA runs were partially covered by a grant from Seven Bridges Genomics for use of the Cancer Genomics Cloud.
The authors declare no competing financial interests.
Supplementary Methods (PDF 200 kb)
Comparison of Recount with GTEx (PDF 4173 kb)
Recount Meta-Analysis (PDF 247 kb)
Recount (gene and exon analyses) (PDF 69269 kb)
Recount (DER analyses) (PDF 25233 kb)
Recount (overly two studies) (PDF 11891 kb)
Recount-analyses repo code (ZIP 241174 kb)
Recount-website (ZIP 36097 kb)
Nellore/runs (ZIP 264948 kb)
Recount-contributions (ZIP 3 kb)
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Collado-Torres, L., Nellore, A., Kammers, K. et al. Reproducible RNA-seq analysis using recount2. Nat Biotechnol 35, 319–321 (2017). https://doi.org/10.1038/nbt.3838
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