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Osborne Robinson
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1 A B Normalized Count Density Density -10 CC A T A T C A T C A T C T AA 5' Fragment End A T C CT AA TC AC CTA T -5 0 CC AT TAC AC T T Supplementary Figure S1 A TA C C TCT TC TC CA C A AAAT TC CT TAA 5 10 TA C TA TA TA TA TA TA TA TA CTA C CCCCCCC CTA TA CTA TA TA TA CAT CAT CAT TA CCCC CT C A T A TC CA TA TCA TC C T C CT CA TC TC C A A TA TT C T C AT T C AAA T AACA CT AC AT AC T AC C A T T AC T AC T A C CTA TA AT C CAT TA TA CAT AT CAT C AT AT TC C CC CCAA T T C CA TC AT AT AT AT AT CAT CAT AT C CAT CAT ACCCCC ' Fragment End C Expected Density TA TA TA TA TA TA TA TA TA TA TA TA TA TA TA TA TA TA TA TA TA TA TA CCCCCCCCC CCCCCCCCC CCCCC AT C CAT CAT CAT CAT AT C CAT CAT CAT CAT AT C CAT CAT CAT CAT AT C CAT CAT CAT CAT AT C CAT CAT D Ratio () This plot shows nucleotide frequencies surrounding the fragment ends for the control experiment in Levin, et al Note that the 3 sequences are complemented in order to represent that nucleotides that are being primed in second-strand synthesis. See Figure 2 in the main text for more details. 1

2 2 A. Roberts, C. Trapnell, J Donaghey, J. Rinn and L. Pachter Supplementary Figure S2 The panels below show the inferred bias for each experiment mentioned in the main text. The first can be used as a legend to help interpret the meaning of each plot. Note that the interpreation of the plots in the second row of each figure is identical to Figure 2 (D) of the main text. Dataset Information Dataset Name/Accession Read Type Strand-Specificity Sample 5' Sequence Bias A C T 5' Positional Bias bp bp bp bp > 4389 bp Fragment Length Distribution Empirical = Learned From Data Estimated = Truncated aussian 3' Sequence Bias A C T 3' Positional Bias bp bp bp bp > 4389 bp SRA bp Paired-End MAQC HBR

3 Improving RNA-Seq expression estimates by correcting for fragment bias 3 SRA010153_HBR 35bp Single-End MAQC HBR NSR 34bp Single-End MAQC HBR

4 4 A. Roberts, C. Trapnell, J Donaghey, J. Rinn and L. Pachter SRA010153_UHR 35bp Single-End MAQC UHR SOLiD4_HBR_PE_50x25 50x25bp Paired-End Second Strand Only MAQC HBR

5 Improving RNA-Seq expression estimates by correcting for fragment bias 5 SOLiD4_UHR_PE_50x25 50x25bp Paired-End Second Strand Only MAQC UHR SRA bp Single-End MAQC UHR

6 6 A. Roberts, C. Trapnell, J Donaghey, J. Rinn and L. Pachter SRA001149_dT_tech 35bp Single-End Yeast BY SRA001149_dT_bio 35bp Single-End Yeast BY

7 Improving RNA-Seq expression estimates by correcting for fragment bias 7 SRA020818_RH 75bp Paired-End Yeast SRA020818_dUTP 75bp Paired-End First Strand Only Yeast

8 8 A. Roberts, C. Trapnell, J Donaghey, J. Rinn and L. Pachter SRA020818_rna_ligation 75bp Single-End Second Strand Only Yeast

9 Improving RNA-Seq expression estimates by correcting for fragment bias 9 SRA020818_ill_ligation 75bp Single-End Second Strand Only Yeast SRA020818_NNSR 73bp Paired-End First Strand Only Yeast

10 10 A. Roberts, C. Trapnell, J Donaghey, J. Rinn and L. Pachter Supplementary Figure S3 Initial Estimates Corrected Estimates Cufflinks FPKM R 2 = R 2 = enominator RPKM R 2 = R 2 = mseq RPKM R 2 = 0.73 R 2 = Plots showing the correlation between the TaqMan qpcr data and RNA-Seq expression estimates before (left) and after (right) the three correction methods compared in the text.

11 Improving RNA-Seq expression estimates by correcting for fragment bias 11 Supplementary Figure S4 Normalized NanoString Count R 2 = Cufflinks FPKM We compared our expression estimates to NanoString on a set of 95 genes, where for each gene we performed a NanoString experiment (see Methods). Although the overall correlation was good (R 2 = 0.77), we could not explain a number of outliers (circled), and we also did not find an improvement in correlation when correcting for bias (in contrast to the case with qrt-pcr that we elaborate on in the main text and all other validations we attempted). Furthermore, we noticed high variance between replicates (see Data). We report these data because of its value in assessing expression accuracy in conjunction with previously generated data reported in Trapnell et al

Supplemental Information. Discovery of Reactive Microbiota-Derived. Metabolites that Inhibit Host Proteases

Supplemental Information. Discovery of Reactive Microbiota-Derived. Metabolites that Inhibit Host Proteases Cell, Volume 168 Supplemental Information Discovery of Reactive Microbiota-Derived Metabolites that Inhibit Host Proteases Chun-Jun Guo, Fang-Yuan Chang, Thomas P. Wyche, Keriann M. Backus, Timothy M.