Data visualization helps engineers “see” more

As single-cell technologies continue to improve, it has become possible to measure multiple parameters simultaneously at the cellular- and even subcellular- level. Flow cytometry, for example, allows for the measurement of hundreds of properties for each cell, including features related to its shape, size, and protein expression levels. This new information has allowed for the discovery of behaviors that were previously unseen using population measures, such as Western blotting.

Example of data visualization (Source: http://www.flickr.com/photos/luc/5418037955/)

Example of data visualization (Source: http://www.flickr.com/photos/luc/5418037955/)

Along with this new information, however, comes a challenge. With multiple dimensions of data, it is difficult to perceive and properly interpret the message presented. Because of this, much of the information gained from single-cell resolution can be obscured or completely lost depending on the way the data are presented.

This perception problem leads to the need for dimension reduction, or a method that can transform the multi-dimensional data into a dataset with only two or three dimensions. To do this, a technique, “t-SNE”  was developed to visualize multi-dimensional data through the identifications of similar clusters within the dataset. t-SNE works by minimizing the differences between data points in order to identify the regions where data are most similar. Once these similarities are identified, t-SNE remaps the multi-dimensional data into three dimensions for visualization – two arbitrary axes and color, for visual separation of clusters. This remapping of the data allows for visual identification of the difference in data points that would be nearly impossible to show with the data in its original form.

One current application of t-SNE, a joint effort from groups in Stanford and Columbia University, uses this data visualization technique to show the heterogeneity in leukemia, and even the tumor subtypes they believe are responsible for relapse. This group took bone marrow samples from individuals who were considered healthy and those with leukemia, and compared these samples using flow cytometry.

With flow cytometry, they were able to study the expression of 29 different proteins, as well as the morphologic features of each cell. After processing the data using t-SNE, the group was able to not only distinguish the healthy cells from the cancerous cells, but also identify the protein expression profiles that were associated with relapse in these patients.

Data visualization is an increasingly important area of research as the amount of information gained from each experiment continues to increase. t-SNE is only one example of many that aims to allow for better perception of high dimension data to maximize its impact. This highlights the need for a researcher to not only design well-planned experiments, but also be creative with the presentation of their data. Creativity, combined with interesting data, will allow for a more thorough presentation of information and ultimately foster a better understanding of many areas in biologic research today, from genomic data to single-cell technologies.

Jacob Sarneki is a second year PhD student in Dr. Wirtz’s lab working on quantification of signal transduction at single cell resolution.

Recent publications from the Johns Hopkins Physical Sciences-Oncology Center

Johns Hopkins Physical Sciences-Oncology Center has had a productive quarter publishing from February to May 2013. Here are some of the most recent publications in support or the center’s core research projects, including a huge collaborative work drawing on the knowledge and research findings of the entire PS-OC network.

Screen Shot 2013-05-15 at 4.27.37 PMThat paper, A physical sciences network characterization of non-tumorigenic and metastatic cells, was the work of 95 authors from all 12 of the National Cancer Institute’s PS-OC  program centers. JHU’s PS-OC director Denis Wirtz, the Theophilus H. Smoot Professor in the Johns Hopkins Department of Chemical and Ciomolecular Engineering, is the corresponding author on this massive effort. We will be discussing the findings of that paper in a future post here on the PS-OC website. Until then, here is a link to that network paper and 13 other recent publications from the Johns Hopkins PS-OC.

  • A physical sciences network characterization of non-tumorigenic and metastatic cells.Physical Sciences – Oncology Centers Network, Agus DB, Alexander JF, Arap W,Ashili S, Aslan JE, Austin RH, Backman V, Bethel KJ, Bonneau R, Chen WC,Chen-Tanyolac C, Choi NC, Curley SA, Dallas M, Damania D, Davies PC, Decuzzi P,Dickinson L, Estevez-Salmeron L, Estrella V, Ferrari M, Fischbach C, Foo J,Fraley SI, Frantz C, Fuhrmann A, Gascard P, Gatenby RA, Geng Y, Gerecht S,Gillies RJ, Godin B, Grady WM, Greenfield A, Hemphill C, Hempstead BL, HielscherA, Hillis WD, Holland EC, Ibrahim-Hashim A, Jacks T, Johnson RH, Joo A, Katz JE,Kelbauskas L, Kesselman C, King MR, Konstantopoulos K, Kraning-Rush CM, Kuhn P,Kung K, Kwee B, Lakins JN, Lambert G, Liao D, Licht JD, Liphardt JT, Liu L, LloydMC, Lyubimova A, Mallick P, Marko J, McCarty OJ, Meldrum DR, Michor F,Mumenthaler SM, Nandakumar V, O’Halloran TV, Oh S, Pasqualini R, Paszek MJ,Philips KG, Poultney CS, Rana K, Reinhart-King CA, Ros R, Semenza GL, Senechal P,Shuler ML, Srinivasan S, Staunton JR, Stypula Y, Subramanian H, Tlsty TD, TormoenGW, Tseng Y, van Oudenaarden A, Verbridge SS, Wan JC, Weaver VM, Widom J, Will C, Wirtz D, Wojtkowiak J, Wu PH.  Sci Rep. 2013 Apr 25;3:1449. doi:10.1038/srep01449. PubMed PMID: 23618955; PubMed Central PMCID: PMC3636513. http://www.ncbi.nlm.nih.gov/pubmed/23618955
  • Procollagen Lysyl Hydroxylase 2 Is Essential for Hypoxia-Induced Breast Cancer Metastasis. Gilkes DM, Bajpai S, Wong CC, Chaturvedi P, Hubbi ME, Wirtz D, Semenza GL.Mol Cancer Res. 2013 May 7. [Epub ahead of print] PubMed PMID: 23378577. http://www.ncbi.nlm.nih.gov/pubmed/23378577
  • Predicting how cells spread and migrate: Focal adhesion size does matter. Kim DH, Wirtz D. Cell Adh Migr. 2013 Apr 29;7(3). [Epub ahead of print] PubMed PMID: 23628962. http://www.ncbi.nlm.nih.gov/pubmed/23628962
  • Hypoxia-inducible Factor 1 (HIF-1) Promotes Extracellular Matrix Remodeling under Hypoxic Conditions by Inducing P4HA1, P4HA2, and PLOD2 Expression in Fibroblasts. Gilkes DM, Bajpai S, Chaturvedi P, Wirtz D, Semenza GL. J Biol   Chem. 2013 Apr 12;288(15):10819-29. doi: 10.1074/jbc.M112.442939. Epub 2013 Feb 19. PubMed PMID: 23423382; PubMed Central PMCID: PMC3624462. http://www.ncbi.nlm.nih.gov/pubmed/23423382
  • Perivascular cells in blood vessel regeneration. Wanjare M, Kusuma S, Gerecht S. Biotechnol J. 2013 Apr;8(4):434-47. doi: 10.1002/biot.201200199. PubMed PMID: 23554249. http://www.ncbi.nlm.nih.gov/pubmed/23554249
  • Focal adhesion size uniquely predicts cell migration. Kim DH, Wirtz D. FASEB J. 2013 Apr;27(4):1351-61. doi: 10.1096/fj.12-220160. Epub 2012 Dec 19. PubMed PMID: 23254340; PubMed Central PMCID: PMC3606534. http://www.ncbi.nlm.nih.gov/pubmed/23254340
  • Notch4-dependent Antagonism of Canonical TGFβ1  Signaling Defines Unique Temporal Fluctuations of SMAD3 Activity in Sheared Proximal Tubular Epithelial Cells. Grabias BM, Konstantopoulos K. Am J Physiol Renal Physiol. 2013 Apr 10. [Epub ahead of print] PubMed PMID: 23576639. http://www.ncbi.nlm.nih.gov/pubmed/23576639
  • Integration and regression of implanted engineered human vascular networks during deep wound healing. Hanjaya-Putra D, Shen YI, Wilson A, Fox-Talbot K, Khetan S, Burdick JA, Steenbergen C, Gerecht S. Stem Cells Transl Med. 2013 Apr;2(4):297-306. doi: 10.5966/sctm.2012-0111. Epub 2013 Mar 13. PubMed PMID: 23486832. http://www.ncbi.nlm.nih.gov/pubmed/23486832
  • Collagen Prolyl Hydroxylases are Essential for Breast Cancer Metastasis. Gilkes DM, Chaturvedi P, Bajpai S, Wong CC, Wei H, Pitcairn S, Hubbi ME, Wirtz D, Semenza GL. Cancer Res. 2013 Mar 28. [Epub ahead of print] PubMed PMID: 23539444. http://www.ncbi.nlm.nih.gov/pubmed/23539444
  • Simultaneously defining cell phenotypes, cell cycle, and chromatin modifications at single-cell resolution.Chambliss AB, Wu PH, Chen WC, Sun SX, Wirtz D.FASEB J. 2013 Mar 28. [Epub ahead of print] PubMed PMID: 23538711.http://www.ncbi.nlm.nih.gov/pubmed/23538711
  • Interstitial friction greatly impacts membrane mechanics. Wirtz D. Biophys J.2013 Mar 19;104(6):1217-8. doi: 10.1016/j.bpj.2013.02.003. Epub 2013 Mar 19.PubMed PMID: 23528079; PubMed Central PMCID: PMC3602747.http://www.ncbi.nlm.nih.gov/pubmed/23528079
  • Functional interplay between the cell cycle and cell phenotypes. Chen WC, Wu PH, Phillip JM, Khatau SB, Choi JM, Dallas MR, Konstantopoulos K,Sun SX, Lee JS, Hodzic D, Wirtz D.Integr Biol (Camb). 2013 Mar;5(3):523-34. doi:10.1039/c2ib20246h. PubMed PMID: 23319145 http://www.ncbi.nlm.nih.gov/pubmed/23319145
  • High-throughput secretomic analysis of single cells to assess functional cellular heterogeneity. Lu Y, Chen JJ, Mu L, Xue Q, Wu Y, Wu PH, Li J, Vortmeyer AO, Miller-Jensen K, Wirtz D, Fan R. Anal Chem. 2013 Feb 19;85(4):2548-56. doi:10.1021/ac400082e. Epub 2013 Feb 1. PubMed PMID: 23339603; PubMed Central PMCID:  PMC3589817.http://www.ncbi.nlm.nih.gov/pubmed/23339603\