Multi-laboratory validation of DNAxs including the statistical library DNAStatistX

被引:4
|
作者
Benschop, Corina C. G. [1 ]
Hoogenboom, Jerry [1 ]
Bargeman, Fiep [1 ]
Hovers, Pauline [1 ]
Slagter, Martin [1 ]
van der Linden, Jennifer [1 ]
Parag, Raymond [1 ]
Kruise, Dennis [2 ]
Drobnic, Katja [3 ]
Klucevsek, Gregor [3 ]
Parson, Walther [4 ,5 ]
Berger, Burkhard [4 ]
Laurent, Francois Xavier [6 ]
Faivre, Magalie [6 ]
Ulus, Ayhan [6 ]
Schneider, Peter [7 ]
Bogus, Magdalena [7 ]
Kneppers, Alexander L. J. [1 ]
Sijen, Titia [1 ]
机构
[1] Netherlands Forens Inst, Div Biol Traces, Laan Van Ypenburg 6, NL-2497 GB The Hague, Netherlands
[2] Netherlands Forens Inst, Div Digital & Biometr Traces, The Hague, Netherlands
[3] Minist Interior, Natl Forens Lab, Ljubljana, Slovenia
[4] Med Univ Innsbruck, Inst Legal Med, Innsbruck, Austria
[5] Penn State Univ, Forens Sci Program, University Pk, PA USA
[6] Inst Natl Police Sci, Ecully, France
[7] Univ Hosp Cologne, Inst Legal Med, Div Forens Mol Genet, Cologne, Germany
关键词
DNA profile interpretation; Likelihood ratio; Continuous model; Validation; DNAxs; DNAStatistX; SOFTWARE; CONTRIBUTORS;
D O I
10.1016/j.fsigen.2020.102390
中图分类号
Q3 [遗传学];
学科分类号
071007 ; 090102 ;
摘要
This study describes a multi-laboratory validation of DNAxs, a DNA eXpert System for the data management and probabilistic interpretation of DNA profiles D. and its statistical library DNAStatistX to which, besides the organising laboratory, four laboratories participated. The software was modified to read multiple data formats and the study was performed prior to the release of the software to the forensic community. The first exercise explored all main functionalities of DNAxs with feedback on user-friendliness, installation and general performance. Next, every laboratory performed likelihood ratio (LR) calculations using their own dataset and a dataset provided by the organising laboratory. The organising laboratory performed LR calculations using all datasets. The datasets were generated with different STR typing kits or analysis systems and consisted of samples varying in DNA amounts, mixture ratios, number of contributors and drop-out level. Hypothesis sets had the correct, under- and over-assigned number of contributors and true and false donors as person of interest. When comparing the results between laboratories, the LRs were foremost within one unit on log10 scale. The few LR results that deviated more had differences for the parameters estimated by the optimizer within DNAStatistX. Some of these were indicated by failed iteration results, others by a failed model validation, since unrealistic hypotheses were included. When these results that do not meet the quality criteria were excluded, as is in accordance with interpretation guidelines, none of the analyses in the different laboratories yielded a different statement in the casework report. Nonetheless, changes in software parameters were sought that minimized differences in outcomes, which made the DNAStatistX module more robust. Overall, the software was found intuitive, user-friendly and valid for use in multiple laboratories.
引用
收藏
页数:10
相关论文
共 50 条
  • [31] Multi-laboratory Validation Study of the Vitrigel-Eye Irritancy Test Method as an Alternative to In Vivo Eye Irritation Testing
    Kojima, Hajime
    Yamaguchi, Hiroyuki
    Sozu, Takashi
    Kleinstreuer, Nicole
    Chae-Hyung, Lim
    Chen, Wannhsin
    Watanabe, Mika
    Fukuda, Takayuki
    Yamashita, Kunihiko
    Takezawa, Toshiaki
    ATLA-ALTERNATIVES TO LABORATORY ANIMALS, 2019, 47 (3-4): : 140 - 157
  • [32] Lane Change Test: Preliminary Results of a Multi-Laboratory Calibration Study
    Bengler, Klaus
    Mattes, Stefan
    Hamm, Otmar
    Hensel, Martin
    PERFORMANCE METRICS FOR ASSESSING DRIVER DISTRACTION: THE QUEST FOR IMPROVED ROAD SAFETY, 2010, : 243 - 253
  • [33] Recommendations following a multi-laboratory comparison of microbial source tracking methods
    Stewart, Jill R.
    Boehm, Alexandria B.
    Dubinsky, Eric A.
    Fong, Theng-Theng
    Goodwin, Kelly D.
    Griffith, John F.
    Noble, Rachel T.
    Shanks, Orin C.
    Vijayavel, Kannappan
    Weisberg, Stephen B.
    WATER RESEARCH, 2013, 47 (18) : 6829 - 6838
  • [34] Quantitative carbohydrate analysis: Results of a multi-laboratory benchmarking exercise.
    Siemiatkoski, JW
    GLYCOBIOLOGY, 2004, 14 (11) : 1203 - 1203
  • [35] Multi-laboratory performance assessment of diffuse optics instruments: the BitMap exercise
    Lanka, Pranav
    Yang, Lin
    Orive-Miguel, David
    Veesa, Joshua Deepak
    Tagliabue, Susanna
    Sudakou, Aleh
    Samaei, Saeed
    Forcione, Mario
    Kovacsova, Zuzana
    Behera, Anurag
    Gladytz, Thomas
    Grosenick, Dirk
    Herve, Lionel
    Durduran, Turgut
    Bejm, Karolina
    Morawiec, Magdalena
    Kacprzak, Michal
    Sawosz, Piotr
    Gerega, Anna
    Liebert, Adam
    Belli, Antonio
    Tachtsidis, Ilias
    Lange, Frederic
    Bale, Gemma
    Baratelli, Luca
    Gioux, Sylvain
    Alexander, Kalyanov
    Wolf, Martin
    Sekar, Sanathana Konugolu Venkata
    Zanoletti, Marta
    Pirovano, Ileana
    Lacerenza, Michele
    Qiu, Lina
    Ferocino, Edoardo
    Maffeis, Giulia
    Amendola, Caterina
    Colombo, Lorenzo
    Frabasile, Lorenzo
    Levoni, Pietro
    Buttafava, Mauro
    Renna, Marco
    Di Sieno, Laura
    Re, Rebecca
    Farina, Andrea
    Spinelli, Lorenzo
    Dalla Mora, Alberto
    Contini, Davide
    Taroni, Paola
    Tosi, Alberto
    Torricelli, Alessandro
    JOURNAL OF BIOMEDICAL OPTICS, 2022, 27 (07)
  • [36] MULTI-LABORATORY STUDY OF MEASUREMENT OF CHLOROBIPHENYLS AND OTHER ORGANOCHLORINES IN FISH OIL
    UTHE, JF
    MUSIAL, CJ
    MISRA, RK
    JOURNAL OF THE ASSOCIATION OF OFFICIAL ANALYTICAL CHEMISTS, 1988, 71 (02): : 369 - 372
  • [37] Results from a multi-laboratory comparison of hydrogen volumetric capacity measurements
    Hurst, Katherine
    Gennett, Thomas
    Parilla, Philip
    ABSTRACTS OF PAPERS OF THE AMERICAN CHEMICAL SOCIETY, 2018, 255
  • [38] Factor V inhibitors: rare or not so uncommon? A multi-laboratory investigation
    Favaloro, EJ
    Posen, J
    Ramakrishna, R
    Soltani, S
    McRae, S
    Just, S
    Aboud, M
    Low, J
    Gemmell, R
    Kershaw, G
    Coleman, R
    Dean, M
    BLOOD COAGULATION & FIBRINOLYSIS, 2004, 15 (08) : 637 - 647
  • [39] Multi-laboratory evaluation of HCG on the automated immunoassay system Elecsys(R).
    Ehrhardt, V
    Ebert, C
    CLINICAL CHEMISTRY, 1997, 43 : 370 - 370
  • [40] The development of gaze following in monolingual and bilingual infants: A multi-laboratory study
    Byers-Heinlein, Krista
    Tsui, Rachel Ka-Ying
    van Renswoude, Daan
    Black, Alexis K.
    Barr, Rachel
    Brown, Anna
    Colomer, Marc
    Durrant, Samantha
    Gampe, Anja
    Gonzalez-Gomez, Nayeli
    Hay, Jessica F.
    Hernik, Mikolaj
    Jarto, Marianna
    Kovacs, Agnes Melinda
    Laoun-Rubenstein, Alexandra
    Lew-Williams, Casey
    Liszkowski, Ulf
    Liu, Liquan
    Noble, Claire
    Potter, Christine E.
    Rocha-Hidalgo, Joscelin
    Sebastian-Galles, Nuria
    Soderstrom, Melanie
    Visser, Ingmar
    Waddell, Connor
    Wermelinger, Stephanie
    Singh, Leher
    INFANCY, 2021, 26 (01) : 4 - 38