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Reproducible RNA-seq analysis using recount2

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Figure 1: Meta-analysis and study comparison facilitated by recount2.
Figure 2: Multi-feature-level differential expression analysis is facilitated by recount2.


  1. 1

    Albers, C.A. et al. Nat. Genet. 44, 435–439, S431–432 (2012).

    CAS  Article  Google Scholar 

  2. 2

    Kohen, R., Dobra, A., Tracy, J.H. & Haugen, E. Transl. Psychiatry 4, e366 (2014).

    CAS  Article  Google Scholar 

  3. 3

    Goh, G. et al. Nat. Genet. 46, 613–617 (2014).

    CAS  Article  Google Scholar 

  4. 4

    Melé, M. et al. Science 348, 660–665 (2015).

    Article  Google Scholar 

  5. 5

    Kodama, Y., Shumway, M. & Leinonen, R. Nucleic Acids Res. 40, D54–D56 (2012).

    CAS  Article  Google Scholar 

  6. 6

    1000 Genomes Project Consortium et al. Nature 467, 1061–1073 (2010).

  7. 7

    Lek, M. et al. Nature 536, 285–291 (2016).

    CAS  Article  Google Scholar 

  8. 8

    Barrett, T. et al. Nucleic Acids Res. 39, D1005–D1010 (2011).

    CAS  Article  Google Scholar 

  9. 9

    Nookaew, I. et al. Nucleic Acids Res. 40, 10084–10097 (2012).

    CAS  Article  Google Scholar 

  10. 10

    Dobin, A. et al. Bioinformatics 29, 15–21 (2013).

    CAS  Article  Google Scholar 

  11. 11

    Kim, D. et al. Genome Biol. 14, R36 (2013).

    Article  Google Scholar 

  12. 12

    Engström, P.G. et al. Nat. Methods 10, 1185–1191 (2013).

    Article  Google Scholar 

  13. 13

    Kumar, P.K., Hoang, T.V., Robinson, M.L., Tsonis, P.A. & Liang, C. Sci. Rep. 5, 13443 (2015).

    CAS  Article  Google Scholar 

  14. 14

    Gentleman, R.C. et al. Genome Biol. 5, R80 (2004).

    Article  Google Scholar 

  15. 15

    Frazee, A.C., Langmead, B. & Leek, J.T. BMC Bioinformatics 12, 449 (2011).

    Article  Google Scholar 

  16. 16

    Love, M.I., Huber, W. & Anders, S. Genome Biol. 15, 550 (2014).

    Article  Google Scholar 

  17. 17

    Law, C.W., Chen, Y., Shi, W. & Smyth, G.K. Genome Biol. 15, R29 (2014).

    Article  Google Scholar 

  18. 18

    Paulson, J.N., Stine, O.C., Bravo, H.C. & Pop, M. Nat. Methods 10, 1200–1202 (2013).

    CAS  Article  Google Scholar 

  19. 19

    Iancu, O.D. et al. Bioinformatics 28, 1592–1597 (2012).

    CAS  Article  Google Scholar 

  20. 20

    Gibbons, J.G., Branco, A.T., Yu, S. & Lemos, B. Nat. Commun. 5, 4850 (2014).

    CAS  Article  Google Scholar 

  21. 21

    Nellore, A. et al. Bioinformatics (2016).

  22. 22

    Nellore, A., Wilks, C., Hansen, K.D., Leek, J.T. & Langmead, B. Bioinformatics 32, 2551–2553 (2016).

    CAS  Article  Google Scholar 

  23. 23

    Collado-Torres, L. et al. Nucleic Acids Res. 45, e9 (2017).

    Article  Google Scholar 

  24. 24

    GTEx Consortium, G. et al. Science 348, 648–660 (2015).

    Article  Google Scholar 

  25. 25

    Kim, S.K. et al. Mol. Oncol. 8, 1653–1666 (2014).

    CAS  Article  Google Scholar 

  26. 26

    Haberman, Y. et al. J. Clin. Invest. 124, 3617–3633 (2014).

    CAS  Article  Google Scholar 

  27. 27

    Smyth, G.K. in Bioinformatics and Computational Biology Solutions using R and Bioconductor 397–420 (Springer, 2005).

    Book  Google Scholar 

  28. 28

    Eswaran, J. et al. Sci. Rep. 3, 1689 (2013).

    Article  Google Scholar 

  29. 29

    Kalari, K.R. et al. PLoS One 8, e79298 (2013).

    CAS  Article  Google Scholar 

  30. 30

    Ignatiadis, N., Klaus, B., Zaugg, J.B. & Huber, W. Nat. Methods 13, 577–580 (2016).

    CAS  Article  Google Scholar 

  31. 31

    Simmons, J.P., Nelson, L.D. & Simonsohn, U. Psychol. Sci. 22, 1359–1366 (2011).

    Article  Google Scholar 

  32. 32

    Petryszak, R. et al. Nucleic Acids Res. 44, D746–D752 (2016).

    CAS  Article  Google Scholar 

  33. 33

    Vivian, J. et al. Nat. Biotechnol. 35, 314–316 (2017).

    CAS  Article  Google Scholar 

  34. 34

    Tatlow, P.J. & Piccolo, S.R. Sci. Rep. 6, 39259 (2016).

    CAS  Article  Google Scholar 

  35. 35

    Rahman, M. et al. Bioinformatics 31, 3666–3672 (2015).

    CAS  Article  Google Scholar 

  36. 36

    Nellore, A. et al. Genome Biol. 17, 266 (2016).

    Article  Google Scholar 

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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 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.

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Corresponding authors

Correspondence to Andrew E Jaffe or Ben Langmead or Jeffrey T Leek.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Methods (PDF 200 kb)

Supplementary Note 1

Comparison of Recount with GTEx (PDF 4173 kb)

Supplementary Note 2

Recount Meta-Analysis (PDF 247 kb)

Supplementary Note 3

Recount (gene and exon analyses) (PDF 69269 kb)

Supplementary Note 4

Recount (DER analyses) (PDF 25233 kb)

Supplementary Note 5

Recount (overly two studies) (PDF 11891 kb)

Supplementary Code 1

Recount-analyses repo code (ZIP 241174 kb)

Supplementary Code 2

Recount-website (ZIP 36097 kb)

Supplementary Code 3

Nellore/runs (ZIP 264948 kb)

Supplementary Code 4

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).

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