Tumor- and circulating-free DNA methylation identifies clinically relevant small cell lung cancer subtypes

Abstract

Small cell lung cancer (SCLC) is an aggressive malignancy composed of distinct transcriptional subtypes, but implementing subtyping in the clinic has remained challenging, particularly due to limited tissue availability. Given the known epigenetic regulation of critical SCLC transcriptional programs, we hypothesized that subtype-specific patterns of DNA methylation could be detected in tumor or blood from SCLC patients. Using genomic-wide reduced-representation bisulfite sequencing (RRBS) in two cohorts totaling 179 SCLC patients and using machine learning approaches, we report a highly accurate DNA methylation-based classifier (SCLC-DMC) that can distinguish SCLC subtypes. We further adjust the classifier for circulating-free DNA (cfDNA) to subtype SCLC from plasma. Using the cfDNA classifier (cfDMC), we demonstrate that SCLC phenotypes can evolve during disease progression, highlighting the need for longitudinal tracking of SCLC during clinical treatment. These data establish that tumor and cfDNA methylation can be used to identify SCLC subtypes and might guide precision SCLC therapy.

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References 77

1. 1.

   Horn L, Mansfield AS, Szczesna A, Havel L, Krzakowski M, Hochmair MJ, Huemer F, Losonczy G, Johnson ML, Nishio M, et al. First-Line Atezolizumab plus Chemotherapy in Extensive-Stage Small-Cell Lung Cancer. N Engl J Med. 2018;379:2220-2229.

   Not in our library10.1056/nejmoa1809064 (opens in a new tab)

2. 2.

   Paz-Ares L, Dvorkin M, Chen Y, Reinmuth N, Hotta K, Trukhin D, Statsenko G, Hochmair MJ, Ozguroglu M, Ji JH, et al. Durvalumab plus platinum-etoposide versus platinum-etoposide in first-line treatment of extensive-stage small-cell lung cancer (CASPIAN): a randomised, controlled, open-label, phase 3 trial. Lancet. 2019;394:1929-1939.

   Not in our library10.1016/s0140-6736(19)32222-6 (opens in a new tab)

3. 3.

   Byers LA, Chiappori A, Smit M-AD. Phase 1 study of AMG 119, a chimeric antigen receptor (CAR) T cell therapy targeting DLL3, in patients with relapsed/refractory small cell lung cancer (SCLC). J Clin Oncol. 2019;37:1–TPS8576.

   Not in our library10.1200/jco.2019.37.15_suppl.tps8576 (opens in a new tab)

4. 4.

   Hipp S, Voynov V, Drobits-Handl B, Giragossian C, Trapani F, Nixon AE, Scheer JM, Adam PJ. A Bispecific DLL3/CD3 IgG-Like T-Cell Engaging Antibody Induces Antitumor Responses in Small Cell Lung Cancer. Clin Cancer Res. 2020;26:5258-5268.

   Not in our library10.1158/1078-0432.ccr-20-0926 (opens in a new tab)

5. 5.

   Paz-Ares L, Champiat S, Lai WV, Izumi H, Govindan R, Boyer M, Hummel HD, Borghaei H, Johnson ML, Steeghs N, et al. Tarlatamab, a First-In-Class DLL3-Targeted Bispecific T-Cell Engager, in Recurrent Small Cell Lung Cancer: An Open-Label, Phase I Study. J Clin Oncol. 2023;JCO2202823.

   Not in our library10.1200/jco.22.02823 (opens in a new tab)

6. 6.

   Pietanza MC, Waqar SN, Krug LM, Dowlati A, Hann CL, Chiappori A, Owonikoko TK, Woo KM, Cardnell RJ, Fujimoto J, et al. Randomized, Double-Blind, Phase II Study of Temozolomide in Combination With Either Veliparib or Placebo in Patients With Relapsed-Sensitive or Refractory Small-Cell Lung Cancer. J Clin Oncol. 2018;36:2386-2394.

   Not in our library10.1200/jco.2018.77.7672 (opens in a new tab)

7. 7.

   Howlader N, Forjaz G, Mooradian MJ, Meza R, Kong CY, Cronin KA, Mariotto AB, Lowy DR, Feuer EJ. The Effect of Advances in Lung-Cancer Treatment on Population Mortality. N Engl J Med. 2020;383:640-649.

   Not in our library10.1056/nejmoa1916623 (opens in a new tab)

8. 8.

   Rudin CM, Poirier JT, Byers LA, Dive C, Dowlati A, George J, Heymach JV, Johnson JE, Lehman JM, MacPherson D, et al. Molecular subtypes of small cell lung cancer: a synthesis of human and mouse model data. Nat Rev Cancer. 2019;19:289-297.

   Not in our library10.1038/s41568-019-0133-9 (opens in a new tab)

9. 9.

   Baine MK, Hsieh MS, Lai WV, Egger JV, Jungbluth AA, Daneshbod Y, Beras A, Spencer R, Lopardo J, Bodd F, et al. SCLC Subtypes Defined by ASCL1, NEUROD1, POU2F3, and YAP1: A Comprehensive Immunohistochemical and Histopathologic Characterization. J Thorac Oncol. 2020;15:1823-1835.

   Not in our library10.1016/j.jtho.2020.09.009 (opens in a new tab)

10. 10.

    Gay CM, Stewart CA, Park EM, Diao L, Groves SM, Heeke S, Nabet BY, Fujimoto J, Solis LM, Lu W, et al. Patterns of transcription factor programs and immune pathway activation define four major subtypes of SCLC with distinct therapeutic vulnerabilities. Cancer Cell. 2021;39:346-360.

    Not in our library10.1016/j.ccell.2020.12.014 (opens in a new tab)

11. 11.
    Recurrent WNT pathway alterations are frequent in relapsed small cell lung cancer · 2018

    No notice
12. 12.

    Xie M, Chugh P, Broadhurst H, Lai Z, Whitston D, Paz-Ares L, Gay C, Byers L, Rudin CM, Stewart R, et al. Abstract CT024: Durvalumab (D) + platinum-etoposide (EP) in 1L extensive-stage small-cell lung cancer (ES-SCLC): Exploratory analysis of SCLC molecular subtypes in CASPIAN. Cancer Research. 2022;82:CT024.

    Not in our library10.1158/1538-7445.am2022-ct024 (opens in a new tab)

13. 13.
    Molecular profiles of small cell lung cancer subtypes: Therapeutic implications · 2021

    No notice
14. 14.

    Chen H, Gesumaria L, Park Y-K, Oliver TG, Singer DS, Ge K, Schrump DS. BET Inhibitors Target the SCLC-N Subtype of Small-Cell Lung Cancer by Blocking NEUROD1 Transactivation. Molecular Cancer Research. 2023;21:91-101.

    Not in our library10.1158/1541-7786.mcr-22-0594 (opens in a new tab)

15. 15.

    Small Cell Lung Cancer (2022). 2021.

    Not in our library

16. 16.

    Blackhall F, Frese KK, Simpson K, Kilgour E, Brady G, Dive C. Will liquid biopsies improve outcomes for patients with small-cell lung cancer? The Lancet Oncology. 2018;19:e470-e481.

    Not in our library10.1016/s1470-2045(18)30455-8 (opens in a new tab)

17. 17.

    Church M, Carter L, Blackhall F. Liquid Biopsy in Small Cell Lung Cancer—A Route to Improved Clinical Care? Cells. 2020;9.

    Not in our library10.3390/cells9122586 (opens in a new tab)

18. 18.

    Sivapalan L, Iams WT, Belcaid Z, Scott SC, Niknafs N, Balan A, White JR, Kopparapu P, Cann C, Landon BV, et al. Dynamics of Sequence and Structural Cell-Free DNA Landscapes in Small-Cell Lung Cancer. Clin Cancer Res. 2023;29:2310-2323.

    Not in our library10.1158/1078-0432.ccr-22-2242 (opens in a new tab)

19. 19.

    Drapkin BJ, George J, Christensen CL, Mino-Kenudson M, Dries R, Sundaresan T, Phat S, Myers DT, Zhong J, Igo P, et al. Genomic and Functional Fidelity of Small Cell Lung Cancer Patient-Derived Xenografts. Cancer Discovery. 2018;8:600-615.

    Not in our library10.1158/2159-8290.cd-17-0935 (opens in a new tab)

20. 20.

    Stewart CA, Gay CM, Xi Y, Sivajothi S, Sivakamasundari V, Fujimoto J, Bolisetty M, Hartsfield PM, Balasubramaniyan V, Chalishazar MD, et al. Single-cell analyses reveal increased intratumoral heterogeneity after the onset of therapy resistance in small-cell lung cancer. Nat Cancer. 2020;1:423-436.

    Not in our library10.1038/s43018-019-0020-z (opens in a new tab)

21. 21.
    cfDNA methylome profiling for detection and subtyping of small cell lung cancers · 2022

    No notice
22. 22.

    Fialkoff G, Takahashi N, Sharkia I, Gutin J, Pongor L, Rajan A, Nichols S, Sciuto L, Vilimas R, Graham C, et al. Subtyping of Small Cell Lung Cancer using plasma cell-free nucleosomes. bioRxiv. 2022.

    Not in our library10.1101/2022.06.24.497386 (opens in a new tab)

23. 23.

    Esfahani MS, Hamilton EG, Mehrmohamadi M, Nabet BY, Alig SK, King DA, Steen CB, Macaulay CW, Schultz A, Nesselbush MC, et al. Inferring gene expression from cell-free DNA fragmentation profiles. Nature Biotechnology. 2022;40:585-597.

    Not in our library10.1038/s41587-022-01222-4 (opens in a new tab)

24. 24.

    Gaga M, Chorostowska-Wynimko J, Horvath I, Tammemagi MC, Shitrit D, Eisenberg VH, Liang H, Stav D, Levy Faber D, Jansen M, et al. Validation of Lung EpiCheck, a novel methylation-based blood assay, for the detection of lung cancer in European and Chinese high-risk individuals. Eur Respir J. 2021;57.

    Not in our library10.1183/13993003.02682-2020 (opens in a new tab)

25. 25.

    George J, Lim JS, Jang SJ, Cun Y, Ozretic L, Kong G, Leenders F, Lu X, Fernandez-Cuesta L, Bosco G, et al. Comprehensive genomic profiles of small cell lung cancer. Nature. 2015;524:47-53.

    Not in our library10.1038/nature14664 (opens in a new tab)

26. 26.

    Yoshihara K, Shahmoradgoli M, Martínez E, Vegesna R, Kim H, Torres-Garcia W, Treviño V, Shen H, Laird PW, Levine DA, et al. Inferring tumour purity and stromal and immune cell admixture from expression data. Nature Communications. 2013;4.

    Not in our library10.1038/ncomms3612 (opens in a new tab)

27. 27.

    Chen B, Khodadoust MS, Liu CL, Newman AM, Alizadeh AA. Profiling Tumor Infiltrating Immune Cells with CIBERSORT. Cancer Systems Biology. 2018;243-259.

    Not in our library10.1007/978-1-4939-7493-1_12 (opens in a new tab)

28. 28.

    Cadieux EL, Mensah NE, Castignani C, Tanić M, Wilson GA, Dietzen M, Dhami P, Vaikkinen H, Verfaillie A, Martin CC, et al. Copy number-aware deconvolution of tumor-normal DNA methylation profiles. BioRxiv. 2022.

    Not in our library10.1101/2020.11.03.366252 (opens in a new tab)

29. 29.
    SCLC-CellMiner: A Resource for Small Cell Lung Cancer Cell Line Genomics and Pharmacology Based on Genomic Signatures · 2020

    Not checked
30. 30.
    A Landscape of Pharmacogenomic Interactions in Cancer · 2016

    No notice
31. 31.

    Weirich S, Khella MS, Jeltsch A. Structure, Activity and Function of the Suv39h1 and Suv39h2 Protein Lysine Methyltransferases. Life. 2021;11.

    Not in our library10.3390/life11070703 (opens in a new tab)

32. 32.

    Fuks F. The DNA methyltransferases associate with HP1 and the SUV39H1 histone methyltransferase. Nucleic Acids Research. 2003;31:2305-2312.

    Not in our library10.1093/nar/gkg332 (opens in a new tab)

33. 33.

    Hu X, Estecio MR, Chen R, Reuben A, Wang L, Fujimoto J, Carrot-Zhang J, McGranahan N, Ying L, Fukuoka J, et al. Evolution of DNA methylome from precancerous lesions to invasive lung adenocarcinomas. Nature Communications. 2021;12:687.

    Not in our library10.1038/s41467-021-20907-z (opens in a new tab)

34. 34.

    Van Paemel R, De Koker A, Caggiano C, Morlion A, Mestdagh P, De Wilde B, Vandesompele J, De Preter K. Genome-wide study of the effect of blood collection tubes on the cell-free DNA methylome. Epigenetics. 2021;16:797-807.

    Not in our library10.1080/15592294.2020.1827714 (opens in a new tab)

35. 35.
    Single-cell transcriptomic profiling reveals the tumor heterogeneity of small-cell lung cancer · 2022

    No notice
36. 36.
    ASCL1 and NEUROD1 Reveal Heterogeneity in Pulmonary Neuroendocrine Tumors and Regulate Distinct Genetic Programs · 2016

    Not checked
37. 37.

    Polley E, Kunkel M, Evans D, Silvers T, Delosh R, Laudeman J, Ogle C, Reinhart R, Selby M, Connelly J, et al. Small Cell Lung Cancer Screen of Oncology Drugs, Investigational Agents, and Gene and microRNA Expression. J Natl Cancer Inst. 2016;108.

    Not in our library10.1093/jnci/djw122 (opens in a new tab)

38. 38.

    Tang M, Abbas HA, Negrao MV, Ramineni M, Hu X, Hubert SM, Fujimoto J, Reuben A, Varghese S, Zhang J, et al. The histologic phenotype of lung cancers is associated with transcriptomic features rather than genomic characteristics. Nat Commun. 2021;12:7081.

    Not in our library10.1038/s41467-021-27341-1 (opens in a new tab)

39. 39.

    Zaitsev A, Chelushkin M, Dyikanov D, Cheremushkin I, Shpak B, Nomie K, Zyrin V, Nuzhdina E, Lozinsky Y, Zotova A, et al. Precise reconstruction of the TME using bulk RNA-seq and a machine learning algorithm trained on artificial transcriptomes. Cancer Cell. 2022;40:879-894.

    Not in our library10.1016/j.ccell.2022.07.006 (opens in a new tab)

40. 40.

    Sato Y, Okamoto I, Kameyama H, Kudoh S, Saito H, Sanada M, Kudo N, Wakimoto J, Fujino K, Ikematsu Y, et al. Integrated Immunohistochemical Study on Small-Cell Carcinoma of the Lung Focusing on Transcription and Co-Transcription Factors. Diagnostics (Basel). 2020;10.

    Not in our library10.3390/diagnostics10110949 (opens in a new tab)

41. 41.

    Wu Q, Guo J, Liu Y, Zheng Q, Li X, Wu C, Fang D, Chen X, Ma L, Xu P, et al. YAP drives fate conversion and chemoresistance of small cell lung cancer. Science Advances. 2021;7.

    Not in our library10.1126/sciadv.abg1850 (opens in a new tab)

42. 42.

    Karim NFA, Miao J, Reckamp KL, Gay CM, Byers LA, Zhao Y, Redman MW, Carrizosa DR, Wang W-L, Petty WJ, et al. SWOG S1929: Phase II randomized study of maintenance atezolizumab (A) versus atezolizumab + talazoparib (AT) in patients with SLFN11 positive extensive stage small cell lung cancer (ES-SCLC). Journal of Clinical Oncology. 2023;41:8504.

    Not in our library10.1200/jco.2023.41.16_suppl.8504 (opens in a new tab)

43. 43.

    Poirier JT, Gardner EE, Connis N, Moreira AL, de Stanchina E, Hann CL, Rudin CM. DNA methylation in small cell lung cancer defines distinct disease subtypes and correlates with high expression of EZH2. Oncogene. 2015;34:5869-5878.

    Not in our library10.1038/onc.2015.38 (opens in a new tab)

44. 44.

    Krushkal J, Silvers T, Reinhold WC, Sonkin D, Vural S, Connelly J, Varma S, Meltzer PS, Kunkel M, Rapisarda A, et al. Epigenome-wide DNA methylation analysis of small cell lung cancer cell lines suggests potential chemotherapy targets. Clin Epigenetics. 2020;12:93.

    Not in our library10.1186/s13148-020-00876-8 (opens in a new tab)

45. 45.

    Lin SH, Wang J, Saintigny P, Wu CC, Giri U, Zhang J, Menju T, Diao L, Byers L, Weinstein JN, et al. Genes suppressed by DNA methylation in non-small cell lung cancer reveal the epigenetics of epithelial-mesenchymal transition. BMC Genomics. 2014;15:1079.

    Not in our library10.1186/1471-2164-15-1079 (opens in a new tab)

46. 46.

    Krohn A, Ahrens T, Yalcin A, Plönes T, Wehrle J, Taromi S, Wollner S, Follo M, Brabletz T, Mani SA, et al. Tumor Cell Heterogeneity in Small Cell Lung Cancer (SCLC): Phenotypical and Functional Differences Associated with Epithelial-Mesenchymal Transition (EMT) and DNA Methylation Changes. PLOS ONE. 2014;9:e100249.

    Not in our library10.1371/journal.pone.0100249 (opens in a new tab)

47. 47.

    Wang Z, Yin J, Zhou W, Bai J, Xie Y, Xu K, Zheng X, Xiao J, Zhou L, Qi X, et al. Complex impact of DNA methylation on transcriptional dysregulation across 22 human cancer types. Nucleic Acids Res. 2020;48:2287-2302.

    Not in our library10.1093/nar/gkaa041 (opens in a new tab)

48. 48.
    Pan-cancer circulating tumor DNA detection in over 10,000 Chinese patients · 2021

    Corrected
49. 49.

    Liu MC, Oxnard GR, Klein EA, Swanton C, Seiden MV, Consortium, C. Sensitive and specific multi-cancer detection and localization using methylation signatures in cell-free DNA. Ann Oncol. 2020;31:745-759.

    Not in our library10.1016/j.annonc.2020.02.011 (opens in a new tab)

50. 50.

    Megyesfalvi Z, Gay CM, Popper H, Pirker R, Ostoros G, Heeke S, Lang C, Hoetzenecker K, Schwendenwein A, Boettiger K, et al. Clinical insights into small cell lung cancer: Tumor heterogeneity, diagnosis, therapy, and future directions. CA Cancer J Clin. 2023.

    Not in our library10.3322/caac.21785 (opens in a new tab)

51. 51.

    Kilgour E, Rothwell DG, Brady G, Dive C. Liquid Biopsy-Based Biomarkers of Treatment Response and Resistance. Cancer Cell. 2020;37:485-495.

    Not in our library10.1016/j.ccell.2020.03.012 (opens in a new tab)

52. 52.

    Pongor LS, Tlemsani C, Elloumi F, Arakawa Y, Jo U, Gross JM, Mosavarpour S, Varma S, Kollipara RK, Roper N, et al. Integrative epigenomic analyses of small cell lung cancer cells demonstrates the clinical translational relevance of gene body methylation. iScience. 2022;25:105338.

    Not in our library10.1016/j.isci.2022.105338 (opens in a new tab)

53. 53.

    Pidsley R, Lawrence MG, Zotenko E, Niranjan B, Statham A, Song J, Chabanon RM, Qu W, Wang H, Richards M, et al. Enduring epigenetic landmarks define the cancer microenvironment. Genome Res. 2018;28:625-638.

    Not in our library10.1101/gr.229070.117 (opens in a new tab)

54. 54.

    Stickler S, Rath B, Hochmair M, Lang C, Weigl L, Hamilton G. Changes of protein expression during tumorosphere formation of small cell lung cancer circulating tumor cells. Oncol Res. 2023;31:13-22.

    Not in our library10.32604/or.2022.027281 (opens in a new tab)

55. 55.

    Cai L, Sondhi V, Zhu M, Akbay E, DeBerardinis RJ, Xie Y, Minna JD, Xiao G, Gazdar A. The small cell lung cancer neuroendocrine transdifferentiation explorer. bioRxiv. 2022;2022.2008.2001.502252.

    Not in our library10.1101/2022.08.01.502252 (opens in a new tab)

56. 56.

    Heredia-Mendez AJ, Sanchez-Sanchez G, Lopez-Camarillo C. Reprogramming of the Genome-Wide DNA Methylation Landscape in Three-Dimensional Cancer Cell Cultures. Cancers (Basel). 2023;15.

    Not in our library10.3390/cancers15071991 (opens in a new tab)

57. 57.

    Park S, Hong TH, Hwang S, Jung H-A, Sun J-M, Ahn JS, Ahn M-J, Cho JH, Choi YS, Kim J, et al. Abstract 4546: Comprehensive analysis using transcriptional factor based molecular subtypes and correlation to clinical outcomes in small-cell lung cancer. Cancer Research. 2023;83:4546.

    Not in our library10.1158/1538-7445.am2023-4546 (opens in a new tab)

58. 58.

    Ul Haq S, Schmid S, Aparnathi MK, Hueniken K, Zhan LJ, Sacdalan D, Li JJN, Meti N, Patel D, Cheng D, et al. Cell-free DNA methylation-defined prognostic subgroups in small-cell lung cancer identified by leukocyte methylation subtraction. iScience. 2022;25.

    Not in our library10.1016/j.isci.2022.105487 (opens in a new tab)

59. 59.

    Cristiano S, Leal A, Phallen J, Fiksel J, Adleff V, Bruhm DC, Jensen SØ, Medina JE, Hruban C, White JR, et al. Genome-wide cell-free DNA fragmentation in patients with cancer. Nature. 2019;570:385-389.

    Not in our library10.1038/s41586-019-1272-6 (opens in a new tab)

60. 60.

    Lo YMD, Han DSC, Jiang P, Chiu RWK. Epigenetics, fragmentomics, and topology of cell-free DNA in liquid biopsies. Science. 2021;372.

    Not in our library10.1126/science.aaw3616 (opens in a new tab)

61. 61.

    Chen T, Guestrin C. XGBoost: A Scalable Tree Boosting System. arXiv. 2016.

    Not in our library10.1145/2939672.2939785 (opens in a new tab)

62. 62.
    Trimmomatic: a flexible trimmer for Illumina sequence data · 2014

    No notice
63. 63.

    Patro R, Duggal G, Love MI, Irizarry RA, Kingsford C. Salmon provides fast and bias-aware quantification of transcript expression. Nat Methods. 2017;14:417-419.

    Not in our library10.1038/nmeth.4197 (opens in a new tab)

64. 64.

    Alboukadel K, Marcin K, Przemyslaw B. survminer: Drawing Survival Curves using ‘ggplot2’. 2021.

    Not in our library

65. 65.

    R: A Language and Environment for Statistical Computing. 2021.

    Not in our library

66. 66.

    Meissner A, Mikkelsen TS, Gu H, Wernig M, Hanna J, Sivachenko A, Zhang X, Bernstein BE, Nusbaum C, Jaffe DB, et al. Genome-scale DNA methylation maps of pluripotent and differentiated cells. Nature. 2008;454:766-770.

    Not in our library10.1038/nature07107 (opens in a new tab)

67. 67.

    Gu H, Smith ZD, Bock C, Boyle P, Gnirke A, Meissner A. Preparation of reduced representation bisulfite sequencing libraries for genome-scale DNA methylation profiling. Nat Protoc. 2011;6:468-481.

    Not in our library10.1038/nprot.2010.190 (opens in a new tab)

68. 68.

    Krueger F, Andrews SR. Bismark: a flexible aligner and methylation caller for Bisulfite-Seq applications. Bioinformatics. 2011;27:1571-1572.

    Not in our library10.1093/bioinformatics/btr167 (opens in a new tab)

69. 69.

    Raymond GC, Maureen AS. annotatr: genomic regions in context. Bioinformatics. 2017.

    Not in our library10.1093/bioinformatics/btx183 (opens in a new tab)

70. 70.

    Max K. caret: Classification and Regression Training. 2021.

    Not in our library

71. 71.

    Tianqi C, Tong H, Michael B, Vadim K, Yuan T, Hyunsu C, Kailong C, Rory M, Ignacio C, Tianyi Z, et al. xgboost: Extreme Gradient Boosting. 2021.

    Not in our library

72. 72.

    BSgenome Hsapiens NCBI GRCh38: Full genome sequences for Homo sapiens (GRCh38). 2014.

    Not in our library

73. 73.

    Achim Z, Gabor G. zoo: S3 Infrastructure for Regular and Irregular Time Series. Journal of Statistical Software. 2005;14:1-27.

    Not in our library10.18637/jss.v014.i06 (opens in a new tab)

74. 74.
    pROC: an open-source package for R and S+ to analyze and compare ROC curves · 2011

    No notice
75. 75.

    Alboukadel K. rstatix: Pipe-Friendly Framework for Basic Statistical Tests. 2021.

    Not in our library

76. 76.

    Hadley W. ggplot2: Elegant Graphics for Data Analysis. 2016.

    Not in our library

77. 77.

    Zuguang G, Roland E, Matthias S. Complex heatmaps reveal patterns and correlations in multidimensional genomic data. Bioinformatics. 2016.

    Not in our library10.1093/bioinformatics/btw313 (opens in a new tab)

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