Literature DB >> 25904095

A Data Analysis Pipeline Accounting for Artifacts in Tox21 Quantitative High-Throughput Screening Assays.

Jui-Hua Hsieh1, Alexander Sedykh2, Ruili Huang3, Menghang Xia3, Raymond R Tice4.   

Abstract

A main goal of the U.S. Tox21 program is to profile a 10K-compound library for activity against a panel of stress-related and nuclear receptor signaling pathway assays using a quantitative high-throughput screening (qHTS) approach. However, assay artifacts, including nonreproducible signals and assay interference (e.g., autofluorescence), complicate compound activity interpretation. To address these issues, we have developed a data analysis pipeline that includes an updated signal noise-filtering/curation protocol and an assay interference flagging system. To better characterize various types of signals, we adopted a weighted version of the area under the curve (wAUC) to quantify the amount of activity across the tested concentration range in combination with the assay-dependent point-of-departure (POD) concentration. Based on the 32 Tox21 qHTS assays analyzed, we demonstrate that signal profiling using wAUC affords the best reproducibility (Pearson's r = 0.91) in comparison with the POD (0.82) only or the AC(50) (i.e., half-maximal activity concentration, 0.81). Among the activity artifacts characterized, cytotoxicity is the major confounding factor; on average, about 8% of Tox21 compounds are affected, whereas autofluorescence affects less than 0.5%. To facilitate data evaluation, we implemented two graphical user interface applications, allowing users to rapidly evaluate the in vitro activity of Tox21 compounds.
© 2015 Society for Laboratory Automation and Screening.

Entities:  

Keywords:  Tox21; concentration-response curve; in vitro activity profiling; qHTS data analysis

Mesh:

Substances:

Year:  2015        PMID: 25904095      PMCID: PMC4568956          DOI: 10.1177/1087057115581317

Source DB:  PubMed          Journal:  J Biomol Screen        ISSN: 1087-0571


  22 in total

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2.  Believe it or not: how much can we rely on published data on potential drug targets?

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3.  Using weighted entropy to rank chemicals in quantitative high-throughput screening experiments.

Authors:  Keith R Shockley
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4.  Hierarchical dose-response modeling for high-throughput toxicity screening of environmental chemicals.

Authors:  Ander Wilson; David M Reif; Brian J Reich
Journal:  Biometrics       Date:  2014-01-07       Impact factor: 2.571

5.  Screen for small molecules increasing the mitochondrial membrane potential.

Authors:  Christine R Montague; Aileen Fitzmaurice; Bradley M Hover; Noe A Salazar; Julien P Fey
Journal:  J Biomol Screen       Date:  2013-07-18

6.  Chemical genomics profiling of environmental chemical modulation of human nuclear receptors.

Authors:  Ruili Huang; Menghang Xia; Ming-Hsuang Cho; Srilatha Sakamuru; Paul Shinn; Keith A Houck; David J Dix; Richard S Judson; Kristine L Witt; Robert J Kavlock; Raymond R Tice; Christopher P Austin
Journal:  Environ Health Perspect       Date:  2011-05-04       Impact factor: 9.031

7.  The Cancer Cell Line Encyclopedia enables predictive modelling of anticancer drug sensitivity.

Authors:  Jordi Barretina; Giordano Caponigro; Nicolas Stransky; Kavitha Venkatesan; Adam A Margolin; Sungjoon Kim; Christopher J Wilson; Joseph Lehár; Gregory V Kryukov; Dmitriy Sonkin; Anupama Reddy; Manway Liu; Lauren Murray; Michael F Berger; John E Monahan; Paula Morais; Jodi Meltzer; Adam Korejwa; Judit Jané-Valbuena; Felipa A Mapa; Joseph Thibault; Eva Bric-Furlong; Pichai Raman; Aaron Shipway; Ingo H Engels; Jill Cheng; Guoying K Yu; Jianjun Yu; Peter Aspesi; Melanie de Silva; Kalpana Jagtap; Michael D Jones; Li Wang; Charles Hatton; Emanuele Palescandolo; Supriya Gupta; Scott Mahan; Carrie Sougnez; Robert C Onofrio; Ted Liefeld; Laura MacConaill; Wendy Winckler; Michael Reich; Nanxin Li; Jill P Mesirov; Stacey B Gabriel; Gad Getz; Kristin Ardlie; Vivien Chan; Vic E Myer; Barbara L Weber; Jeff Porter; Markus Warmuth; Peter Finan; Jennifer L Harris; Matthew Meyerson; Todd R Golub; Michael P Morrissey; William R Sellers; Robert Schlegel; Levi A Garraway
Journal:  Nature       Date:  2012-03-28       Impact factor: 49.962

8.  Formalization, annotation and analysis of diverse drug and probe screening assay datasets using the BioAssay Ontology (BAO).

Authors:  Uma D Vempati; Magdalena J Przydzial; Caty Chung; Saminda Abeyruwan; Ahsan Mir; Kunie Sakurai; Ubbo Visser; Vance P Lemmon; Stephan C Schürer
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9.  A three-stage algorithm to make toxicologically relevant activity calls from quantitative high throughput screening data.

Authors:  Keith R Shockley
Journal:  Environ Health Perspect       Date:  2012-05-10       Impact factor: 9.031

Review 10.  Improving the human hazard characterization of chemicals: a Tox21 update.

Authors:  Raymond R Tice; Christopher P Austin; Robert J Kavlock; John R Bucher
Journal:  Environ Health Perspect       Date:  2013-04-19       Impact factor: 9.031

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  27 in total

1.  Integrated Model of Chemical Perturbations of a Biological Pathway Using 18 In Vitro High-Throughput Screening Assays for the Estrogen Receptor.

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Journal:  Toxicol Sci       Date:  2015-08-13       Impact factor: 4.849

2.  Assessment of the DNA damaging potential of environmental chemicals using a quantitative high-throughput screening approach to measure p53 activation.

Authors:  Kristine L Witt; Jui-Hua Hsieh; Stephanie L Smith-Roe; Menghang Xia; Ruili Huang; Jinghua Zhao; Scott S Auerbach; Junguk Hur; Raymond R Tice
Journal:  Environ Mol Mutagen       Date:  2017-07-17       Impact factor: 3.216

3.  Evaluation of androgen assay results using a curated Hershberger database.

Authors:  N C Kleinstreuer; P Browne; X Chang; R Judson; W Casey; P Ceger; C Deisenroth; N Baker; K Markey; R S Thomas
Journal:  Reprod Toxicol       Date:  2018-09-08       Impact factor: 3.143

4.  An Intuitive Approach for Predicting Potential Human Health Risk with the Tox21 10k Library.

Authors:  Nisha S Sipes; John F Wambaugh; Robert Pearce; Scott S Auerbach; Barbara A Wetmore; Jui-Hua Hsieh; Andrew J Shapiro; Daniel Svoboda; Michael J DeVito; Stephen S Ferguson
Journal:  Environ Sci Technol       Date:  2017-09-06       Impact factor: 9.028

5.  The Tox21 10K Compound Library: Collaborative Chemistry Advancing Toxicology.

Authors:  Ann M Richard; Ruili Huang; Suramya Waidyanatha; Paul Shinn; Bradley J Collins; Inthirany Thillainadarajah; Christopher M Grulke; Antony J Williams; Ryan R Lougee; Richard S Judson; Keith A Houck; Mahmoud Shobair; Chihae Yang; James F Rathman; Adam Yasgar; Suzanne C Fitzpatrick; Anton Simeonov; Russell S Thomas; Kevin M Crofton; Richard S Paules; John R Bucher; Christopher P Austin; Robert J Kavlock; Raymond R Tice
Journal:  Chem Res Toxicol       Date:  2020-11-03       Impact factor: 3.739

6.  Cell-Based High-Throughput Screening for Aromatase Inhibitors in the Tox21 10K Library.

Authors:  Shiuan Chen; Jui-Hua Hsieh; Ruili Huang; Srilatha Sakamuru; Li-Yu Hsin; Menghang Xia; Keith R Shockley; Scott Auerbach; Noriko Kanaya; Hannah Lu; Daniel Svoboda; Kristine L Witt; B Alex Merrick; Christina T Teng; Raymond R Tice
Journal:  Toxicol Sci       Date:  2015-07-03       Impact factor: 4.849

Review 7.  Endocrine-disrupting chemicals: economic, regulatory, and policy implications.

Authors:  Christopher D Kassotis; Laura N Vandenberg; Barbara A Demeneix; Miquel Porta; Remy Slama; Leonardo Trasande
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8.  Application of Benchmark Concentration (BMC) Analysis on Zebrafish Data: A New Perspective for Quantifying Toxicity in Alternative Animal Models.

Authors:  Jui-Hua Hsieh; Kristen Ryan; Alexander Sedykh; Ja-An Lin; Andrew J Shapiro; Frederick Parham; Mamta Behl
Journal:  Toxicol Sci       Date:  2019-01-01       Impact factor: 4.849

9.  Channel Interactions and Robust Inference for Ratiometric β-lactamase Assay Data: a Tox21 Library Analysis.

Authors:  Fjodor Melnikov; Jui-Hua Hsieh; Nisha S Sipes; Paul T Anastas
Journal:  ACS Sustain Chem Eng       Date:  2018-01-15       Impact factor: 8.198

10.  Editor's Highlight: Comparative Toxicity of Organophosphate Flame Retardants and Polybrominated Diphenyl Ethers to Caenorhabditis elegans.

Authors:  Mamta Behl; Julie R Rice; Marjo V Smith; Caroll A Co; Matthew F Bridge; Jui-Hua Hsieh; Jonathan H Freedman; Windy A Boyd
Journal:  Toxicol Sci       Date:  2016-08-26       Impact factor: 4.849

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