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Streaming fragment assignment for real-time analysis of sequencing experiments

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We present eXpress, a software package for efficient probabilistic assignment of ambiguously mapping sequenced fragments. eXpress uses a streaming algorithm with linear run time and constant memory use. It can determine abundances of sequenced molecules in real time and can be applied to ChIP-seq, metagenomics and other large-scale sequencing data. We demonstrate its use on RNA-seq data and show that eXpress achieves greater efficiency than other quantification methods.

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Figure 1: Overview of eXpress.
Figure 2: Accuracy and efficiency of eXpress.
Figure 3: Example of abundance estimation by eXpress, RSEM and Cufflinks at different depths of simulated data for the three-isoform human gene UGT3A2 (ρt, relative abundance for target t).

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Sequence Read Archive

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  • 04 December 2012

    In the HTML version of this article initially published online, errors in mathematical terms were present in the Online Methods section. The errors have been corrected in the HTML version.


  1. Lipman, D., Flicek, P., Salzberg, S., Gerstein, M. & Knight, R. Genome Biol. 12, 402 (2011).

    Article  Google Scholar 

  2. Wold, B. & Myers, R.M. Nat. Methods 5, 19–21 (2008).

    CAS  Article  Google Scholar 

  3. Hashimoto, T. et al. Bioinformatics 25, 2613–2614 (2009).

    CAS  Article  Google Scholar 

  4. Li, B. & Dewey, C.N. BMC Bioinformatics 12, 323 (2011).

    CAS  Article  Google Scholar 

  5. Trapnell, C. et al. Nat. Biotechnol. 28, 511–515 (2010).

    CAS  Article  Google Scholar 

  6. Chung, D. et al. PLOS Comput. Biol. 7, e1002111 (2011).

    CAS  Article  Google Scholar 

  7. Meinicke, P., Aßhauer, K.P. & Lingner, T. Bioinformatics 27, 1618–1624 (2011).

    CAS  Article  Google Scholar 

  8. Taub, M., Lipson, D. & Speed, T.P. Commun. Inf. Syst. 10, 69–82 (2010).

    Google Scholar 

  9. Cappé, O. & Moulines, E. J. R. Stat. Soc. Series B Stat. Methodol. 71, 593–613 (2009).

    Article  Google Scholar 

  10. Liang, P. & Klein, D. in Proc. Hum. Lang. Technol. Conf. North Am. Ch. Assoc. Comput. Linguist. 611–619 (ACL, 2009).

  11. Hansen, K.D., Brenner, S.E. & Dudoit, S. Nucleic Acids Res. 38, e131 (2010).

    Article  Google Scholar 

  12. Roberts, A. et al. Genome Biol. 12, R22 (2011).

    CAS  Article  Google Scholar 

  13. Lee, S. et al. Nucleic Acids Res. 39, e9 (2011).

    Article  Google Scholar 

  14. MAQC Consortium. et al. Nat. Biotechnol. 24, 1151–1161 (2006).

  15. Anders, S. & Huber, W. Genome Biol. 11, R106 (2010).

    CAS  Article  Google Scholar 

  16. Trapnell, C. et al. Nat. Biotechnol. (in the press).

  17. Branton, D. et al. Nat. Biotechnol. 26, 1146–1153 (2008).

    CAS  Article  Google Scholar 

  18. Stein, L.D. Genome Biol. 11, 207 (2010).

    Article  Google Scholar 

  19. Langmead, B., Trapnell, C., Pop, M. & Salzberg, S.L. Genome Biol. 10, R25 (2009).

    Article  Google Scholar 

  20. Ahmadi, A. et al. Nucleic Acids Res. 40, e41 (2011).

    Article  Google Scholar 

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This work was supported by US National Institutes of Health grant R01HG006129. A.R. was supported in part by a National Science Foundation graduate research fellowship. We thank H. Pimentel for developing Map2GTF for converting genome mappings to transcriptome mappings and incorporating it into TopHat to help with our analysis.

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Authors and Affiliations



A.R. and L.P. developed the mathematics and statistics and designed the algorithms. A.R. implemented the method in eXpress. A.R. and L.P. tested the software and performed the analysis. A.R. and L.P. wrote the manuscript.

Corresponding author

Correspondence to Lior Pachter.

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The authors declare no competing financial interests.

Supplementary information

Supplementary Text and Figures

Supplementary Figures 1–11 and Supplementary Tables 1 and 2 (PDF 3034 kb)

Supplementary Software

eXpress source code and compiled binary files. (ZIP 3800 kb)

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Roberts, A., Pachter, L. Streaming fragment assignment for real-time analysis of sequencing experiments. Nat Methods 10, 71–73 (2013).

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