The maximum connectivity scores of pairwise chemical conditions summarized from Cmap results in a file with Cytoscape format (http://www.cytoscape.org/). The figures in the publication were generated from this file. The Cytoscape file is formed from importing the eight text file therein. This dataset is associated with the following publication: Wang , R., A. Biales , N. Garcia-Reyero, E. Perkins, D. Villeneuve, G. Ankley, and D. Bencic. Fish Connectivity Mapping: Linking Chemical Stressors by Their MOA-Driven Transcriptomic Profiles. BMC Genomics. BioMed Central Ltd, London, UK, 17(84): 1-20, (2016).

RLWrankedLists.tar.gz:These lists linked to various chemical treatment conditions serve as the target collection of Cmap. Probes of the entire microarray are sorted based on their log fold changes over control conditions. RLWsignatures2015.tar.gz: These signatures linked to various chemical treatment conditions serve as queries in Cmap. This dataset is not publicly accessible because: too big in size. It can be accessed through the following means: located in the High Performance Computing archive /asm/FISHTOX/TAR_BALLs/fishCmap.tar.gz. Format: Fish connectivity mapping involves working with a large amount of data. Of primary interest to other researchers and general public are probably the rank-ordered gene lists and gene signatures. The former acts as a database-like target while the latter as queries. Along with fish Cmap outputs, they are contained in the file fishCmap.tar.gz as RLWrankedLists.tar.gz and RLWsignatures2015.tar.gz. This dataset is associated with the following publication: Wang , R., A. Biales , N. Garcia-Reyero, E. Perkins, D. Villeneuve, G. Ankley, and D. Bencic. Fish Connectivity Mapping: Linking Chemical Stressors by Their MOA-Driven Transcriptomic Profiles. BMC Genomics. BioMed Central Ltd, London, UK, 17(84): 1-20, (2016).

RLWrankedLists.tar.gz:These lists linked to various chemical treatment conditions serve as the target collection of Cmap. Probes of the entire microarray are sorted based on their log fold changes over control conditions. RLWsignatures2015.tar.gz: These signatures linked to various chemical treatment conditions serve as queries in Cmap. This dataset is not publicly accessible because: too big in size. It can be accessed through the following means: located in the High Performance Computing archive /asm/FISHTOX/TAR_BALLs/fishCmap.tar.gz. Format: Fish connectivity mapping involves working with a large amount of data. Of primary interest to other researchers and general public are probably the rank-ordered gene lists and gene signatures. The former acts as a database-like target while the latter as queries. Along with fish Cmap outputs, they are contained in the file fishCmap.tar.gz as RLWrankedLists.tar.gz and RLWsignatures2015.tar.gz. This dataset is associated with the following publication: Wang , R., A. Biales , N. Garcia-Reyero, E. Perkins, D. Villeneuve, G. Ankley, and D. Bencic. Fish Connectivity Mapping: Linking Chemical Stressors by Their MOA-Driven Transcriptomic Profiles. BMC Genomics. BioMed Central Ltd, London, UK, 17(84): 1-20, (2016).

Various Cmap analyses within and across species and microarray platforms conducted and summarized to generate the tables in the publication. This dataset is associated with the following publication: Wang , R., A. Biales , N. Garcia-Reyero, E. Perkins, D. Villeneuve, G. Ankley, and D. Bencic. Fish Connectivity Mapping: Linking Chemical Stressors by Their MOA-Driven Transcriptomic Profiles. BMC Genomics. BioMed Central Ltd, London, UK, 17(84): 1-20, (2016).

Various Cmap analyses within and across species and microarray platforms conducted and summarized to generate the tables in the publication. This dataset is associated with the following publication: Wang , R., A. Biales , N. Garcia-Reyero, E. Perkins, D. Villeneuve, G. Ankley, and D. Bencic. Fish Connectivity Mapping: Linking Chemical Stressors by Their MOA-Driven Transcriptomic Profiles. BMC Genomics. BioMed Central Ltd, London, UK, 17(84): 1-20, (2016).

The data set provides a set of txt files and cytoscape files that were used to construct the example AOP networks included in the paper. Additionally, a supplementary table file provides all the network statistics discussed in the manuscript (e.g., node degree calculations, betweenness centrality, eccentricity, etc.). This dataset is associated with the following publication: Villeneuve, D., M. Angrish, M. Fortin, I. Katsiadaki, M. Leonard, L. Margiotta-Casaluci, S. Munn, J. O'Brien, N. Pollesch, C. Smith, X. Zhang, and D. Knapen. Adverse outcome pathway networks II: Network analytics. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 37(6): 1734-1748, (2018).

The data set provides a set of txt files and cytoscape files that were used to construct the example AOP networks included in the paper. Additionally, a supplementary table file provides all the network statistics discussed in the manuscript (e.g., node degree calculations, betweenness centrality, eccentricity, etc.). This dataset is associated with the following publication: Villeneuve, D., M. Angrish, M. Fortin, I. Katsiadaki, M. Leonard, L. Margiotta-Casaluci, S. Munn, J. O'Brien, N. Pollesch, C. Smith, X. Zhang, and D. Knapen. Adverse outcome pathway networks II: Network analytics. ENVIRONMENTAL TOXICOLOGY AND CHEMISTRY. Society of Environmental Toxicology and Chemistry, Pensacola, FL, USA, 37(6): 1734-1748, (2018).

Previous work identified a ‘cytotoxic burst’ (CTB) phenomenon wherein large numbers of the ToxCast assays begin to respond at or near test chemical concentrations that elicit cytotoxicity, and a statistical approach to defining the bounds of the CTB was developed. To focus AOP development on the molecular targets corresponding to ToxCast assays indicating pathway-specific effects, we conducted a meta-analysis to identify which assays most frequently respond at concentrations below the CTB. A preliminary list of potentially important, target-specific assays was determined by ranking assays by the fraction of chemical hits below the CTB compared to the number of chemicals tested. Additional priority assays were identified using a diagnostic-odds-ratio approach which gives greater ranking to assays with high specificity but low responsivity. Combined, the two prioritization methods identified several novel targets (e.g., peripheral benzodiazepine and progesterone receptors) to prioritize for AOP development, and affirmed the importance of a number of existing AOPs aligned with ToxCast targets (e.g., thyroperoxidase, estrogen receptor, aromatase). This dataset is associated with the following publication: Fay, K., J. Swintek, D. Villeneuve, S. Edwards, M. Nelms, B. Blackwell, and G. Ankley. Differentiating pathway-specific from non-specific effects in high-throughput toxicity data: A foundation for prioritizing adverse outcome pathway development. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 163(2): 500-515, (2018).

Previous work identified a ‘cytotoxic burst’ (CTB) phenomenon wherein large numbers of the ToxCast assays begin to respond at or near test chemical concentrations that elicit cytotoxicity, and a statistical approach to defining the bounds of the CTB was developed. To focus AOP development on the molecular targets corresponding to ToxCast assays indicating pathway-specific effects, we conducted a meta-analysis to identify which assays most frequently respond at concentrations below the CTB. A preliminary list of potentially important, target-specific assays was determined by ranking assays by the fraction of chemical hits below the CTB compared to the number of chemicals tested. Additional priority assays were identified using a diagnostic-odds-ratio approach which gives greater ranking to assays with high specificity but low responsivity. Combined, the two prioritization methods identified several novel targets (e.g., peripheral benzodiazepine and progesterone receptors) to prioritize for AOP development, and affirmed the importance of a number of existing AOPs aligned with ToxCast targets (e.g., thyroperoxidase, estrogen receptor, aromatase). This dataset is associated with the following publication: Fay, K., J. Swintek, D. Villeneuve, S. Edwards, M. Nelms, B. Blackwell, and G. Ankley. Differentiating pathway-specific from non-specific effects in high-throughput toxicity data: A foundation for prioritizing adverse outcome pathway development. TOXICOLOGICAL SCIENCES. Society of Toxicology, RESTON, VA, 163(2): 500-515, (2018).

Algal toxins are a growing concern worldwide. Rapid assessment test strips are a newer technology and their accuracy in detecting toxins in different lakes with different phytoplankton and toxins present is unknown. This data release is supported by our testing of toxin test strips. This research took place in Voyageurs National Park in northern Minnesota. The research will indicate whether these test strips are accurate for this system, and hopefully lay the foundation for a cost-effective harmful algal blooms (HABs) monitoring and communication tool for Voyageurs National Park and other parks. The utility of the test strips in this system may lead to broader applications, for instance in other inland systems like the nearby Lake of the Woods and Isle Royale National Park or other northern temperate lakes.