Obtain Immune, Stroma, ESTIMATE and Tumor Purity scores from a cohort of samples, using the method implemented in Yoshihara et al., 2013.
Arguments
- expr_data
A normalized gene expression matrix (or data frame) with gene symbols as row names and samples as columns.
Value
A tibble with one row for each sample in expr_data and five columns:
sample_id, immune_score, stroma_score, estimate_score and purity_score.
Details
The ESTIMATE (Estimation of STromal and Immune cells in MAlignant Tumors using Expression data) method was developed with the aim to estimate the fraction of tumor cells in a sample by using gene expression instead of copy number data. The fundamental assumption of this method is that the tumor microenvironment is a very rich and dynamic ecosystem, in which immune infiltrating cells and stroma play a major role. The ESTIMATE score is defined as the combination (i.e. sum) of immune and stroma scores and can be thought of as a "non-tumor score". Consequently, a high ESTIMATE enrichment gives a low tumor purity score and viceversa.
Algorithm
Raw immune and stromal signatures scores are computed using single sample GSEA with rank normalization (Barbie et al., 2009). Then, the ESTIMATE score is computed by summing the immune and stroma scores. Finally, the tumor purity score is obtained with the following formula: $$Purity = cos(0.6049872018 + 0.0001467884 * ESTIMATE)$$
References
Barbie, D. A., Tamayo, P., Boehm, J. S., Kim, S. Y., Moody, S. E., Dunn, I. F., Schinzel, A. C., Sandy, P., Meylan, E., Scholl, C., Fröhling, S., Chan, E. M., Sos, M. L., Michel, K., Mermel, C., Silver, S. J., Weir, B. A., Reiling, J. H., Sheng, Q., Gupta, P. B., … Hahn, W. C. (2009). Systematic RNA interference reveals that oncogenic KRAS-driven cancers require TBK1. Nature, 462(7269), 108–112. doi:10.1038/nature08460 .
Yoshihara, K., Shahmoradgoli, M., Martínez, E., Vegesna, R., Kim, H., Torres-Garcia, W., Treviño, V., Shen, H., Laird, P. W., Levine, D. A., Carter, S. L., Getz, G., Stemke-Hale, K., Mills, G. B., & Verhaak, R. G. (2013). Inferring tumour purity and stromal and immune cell admixture from expression data. Nature communications, 4, 2612. doi:10.1038/ncomms3612 .
Examples
hack_estimate(test_expr)
#> # A tibble: 20 × 5
#> sample_id immune_score stroma_score estimate_score purity_score
#> <chr> <dbl> <dbl> <dbl> <dbl>
#> 1 sample1 -636. 778. 142. 0.811
#> 2 sample10 1590. 1297. 2887. 0.516
#> 3 sample11 2040. 512. 2552. 0.557
#> 4 sample12 1835. 772. 2607. 0.551
#> 5 sample13 632. 778. 1409. 0.688
#> 6 sample14 1185. 1005. 2191. 0.601
#> 7 sample15 2393. 415. 2808. 0.526
#> 8 sample16 1308. 1274. 2582. 0.554
#> 9 sample17 1181. 677. 1858. 0.639
#> 10 sample18 851. 1517. 2368. 0.580
#> 11 sample19 1672. 980. 2652. 0.545
#> 12 sample2 2118. 703. 2821. 0.524
#> 13 sample20 1639. 2482. 4121. 0.353
#> 14 sample3 725. 805. 1530. 0.675
#> 15 sample4 737. 2031. 2768. 0.531
#> 16 sample5 181. 1129. 1310. 0.699
#> 17 sample6 1221. 1175. 2395. 0.576
#> 18 sample7 1322. 375. 1697. 0.657
#> 19 sample8 515. 1158. 1673. 0.660
#> 20 sample9 297. 1147. 1443. 0.685