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6. Verification with real-time COSPAN

Author

Courcoubetis, C., Dill, D., Chatzaki, M., Tzounakis, P., Goos, Gerhard, editor, Hartmanis, Juris, editor, von Bochmann, Gregor, editor, and Probst, David Karl, editor

Published
1993
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11. Phlebologie an deutschen Hautkliniken: Eine Bestandsaufnahme im Auftrag der Deutschen Gesellschaft für Phlebologie

Author

Reich-Schupke, S., Alm, J., Altmeyer, P., Bachter, D., Bayerl, C., Beissert, S., Bieber, T., Böhmer, J., Dill, D., Dippel, E., Dücker, P., Effendy, I., El Gammal, S., Elsner, P., Enk, A., Feldmann-Böddeker, I., Frank, H., Gehring, W., Gieler, U., Goebeler, M., Görge, T., Gollnick, H., Grabbe, S., Gross, G., Gudat, W., Happ, A., Herbst, R., Hermes, B., Hoff, N.-P., John, S.M., Jungelhülsing, M., Jünger, M., Kaatz, M., Kapp, A., Kaufmann, R., Klode, J., Knaber, K., König, A., Krieg, T., Kohl, P., Kowalzick, L., Lehmann, P., Löffler, H., Maschke, J., Marsch, W., Mechtel, D., Mohr, P., Moll, I., Müller, M., Nashan, D., Ockenfels, H.M., Peter, R.U., Pillekamp, H., Rompel, R., Ruzicka, T., Salfeld, K., Sander, C., Schaller, J., Scharffetter-Kochanek, K., Schuler, G., Schulze, H.-J., Schwarz, T., Splieth, B., Stege, H., Stolz, W., Strölin, A., Tran, H., Tronnier, M., Ulrich, J., Vogt, T., Wagner, G., Welzel, J., Willgeroth, T., Wollina, U., Zillikens, D., Zouboulis, C.C., Zuberbier, T., Zutt, M., and Stücker, M.

Published
2013
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40. Critical assessment of automated flow cytometry data analysis techniques

Author

Aghaeepour, N, Finak, G, Flowcap, Consortium, Dougall, D, Khodabakhshi, Ah, Mah, P, Obermoser, G, Spidlen, J, Taylor, I, Wuensch, Sa, Bramson, J, Eaves, C, Weng, Ap, Iii, Es, Ho, K, Kollmann, T, Rogers, W, De Rosa, S, Dalal, B, Azad, A, Pothen, A, Brandes, A, Bretschneider, H, Bruggner, R, Finck, R, Jia, R, Zimmerman, N, Linderman, M, Dill, D, Nolan, G, Chan, C, Khettabi, Fe, O'Neill, K, Chikina, M, Ge, Y, Sealfon, S, Sugár, I, Gupta, A, Shooshtari, P, Zare, H, De Jager PL, Jiang, M, Keilwagen, J, Maisog, Jm, Luta, G, Barbo, Aa, Májek, P, Vilček, J, Manninen, T, Huttunen, H, Ruusuvuori, P, Nykter, M, Mclachlan, Gj, Wang, K, Naim, I, Sharma, G, Nikolic, R, Pyne, S, Qian, Y, Qiu, P, Quinn, J, Roth, A, Dream, Consortium, Meyer, P, Stolovitzky, G, Saez Rodriguez, J, Norel, R, Bhattacharjee, M, Biehl, M, Bucher, P, Bunte, K, DI CAMILLO, Barbara, Sambo, Francesco, Sanavia, Tiziana, Trifoglio, Emanuele, Toffolo, GIANNA MARIA, Dimitrieva, S, Dreos, R, Ambrosini, G, Grau, J, Grosse, I, Posch, S, Guex, N, Kursa, M, Rudnicki, W, Liu, B, Maienschein Cline, M, Schneider, P, Seifert, M, Strickert, M, Vilar, Jm, Hoos, H, Mosmann, Tr, Brinkman, R, Gottardo, R, Scheuermann, Rh, Dialogue for Reverse Engineering Assessment and Methods (DREAM) Consortium, Guex, Nicolas, and Abrosini, Giovanna

Subjects
Computer science, Population, Immunology, Graft vs Host Disease, Image processing, Gating, computer.software_genre, Bioinformatics, Biochemistry, Sensitivity and Specificity, Biotechnology, Cell Biology, Molecular Biology, Article, Flow cytometry, 03 medical and health sciences, 0302 clinical medicine, Software, Computational biology and bioinformatics, Immunology, Cancer, Flow cytometry, medicine, Image Processing, Computer-Assisted, Animals, Cluster Analysis, Humans, education, 030304 developmental biology, Cancer, 0303 health sciences, Data processing, education.field_of_study, medicine.diagnostic_test, business.industry, Computational Biology, Reproducibility of Results, Computational biology and bioinformatics, Identification (information), Data Interpretation, Statistical, Data analysis, Leukocytes, Mononuclear, Data mining, Lymphoma, Large B-Cell, Diffuse, business, computer, Algorithms, West Nile Fever, 030215 immunology
Abstract

Traditional methods for flow cytometry (FCM) data processing rely on subjective manual gating. Recently, several groups have developed computational methods for identifying cell populations in multidimensional FCM data. The Flow Cytometry: Critical Assessment of Population Identification Methods (FlowCAP) challenges were established to compare the performance of these methods on two tasks: (i) mammalian cell population identification, to determine whether automated algorithms can reproduce expert manual gating and (ii) sample classification, to determine whether analysis pipelines can identify characteristics that correlate with external variables (such as clinical outcome). This analysis presents the results of the first FlowCAP challenges. Several methods performed well as compared to manual gating or external variables using statistical performance measures, which suggests that automated methods have reached a sufficient level of maturity and accuracy for reliable use in FCM data analysis.

Published
2013

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