An abundance matrix (BM_OTU.xlsx) contains rows as OTU, columns as samples, and entries representing the abundance of each OTU as a ratio of all sequences obtained for each individual sample. This dataset is associated with the following publication: Gomez-Alvarez, V., and R. Revetta. Monitoring of Nitrification in Chloraminated Drinking Water Distribution Systems With Microbiome Bioindicators Using Supervised Machine Learning. Frontiers in Microbiology. Frontiers, Lausanne, SWITZERLAND, 11: 2254-2267, (2020).

An abundance matrix (EX_OTU.xlsx) contains rows as OTU, columns as samples, and entries representing the abundance of each OTU as a ratio of all sequences obtained for each individual sample. This dataset is associated with the following publication: Gomez-Alvarez, V., S. Pfaller, J. Pressman, D. Wahman, and R. Revetta. Resilience of microbial communities in a simulated drinking water distribution system subjected to disturbances: role of conditionally rare taxa and potential implications for antibiotic-resistant bacteria. Environmental Science: Water Research & Technology. Royal Society of Chemistry, Cambridge, UK, 2: 645-657, (2016).

An abundance matrix (PS_taxonomic_lineage.xlsx) contains rows as taxonomic lineage, columns as samples, and entries representing the abundance of each lineage as a ratio of all sequences obtained for each individual sample. This dataset is associated with the following publication: Revetta , R., V. Gomez-Alvarez, T. Gerke, J. Santodomingo , and N. Ashbolt. CHANGES IN BACTERIAL COMPOSITION OF BIOFILM IN A METROPOLITAN DRINKING WATER DISTRIBUTION SYSTEM. JOURNAL OF APPLIED MICROBIOLOGY. Blackwell Publishing, Malden, MA, USA, 121(1): 294-305, (2016).

An abundance matrix (BM_taxonomic_lineage.xlsx) contains rows as taxonomic lineage, columns as samples, and entries representing the abundance of each lineage as a ratio of all sequences obtained for each individual sample. This dataset is associated with the following publication: Gomez-Alvarez, V., and R. Revetta. Monitoring of Nitrification in Chloraminated Drinking Water Distribution Systems With Microbiome Bioindicators Using Supervised Machine Learning. Frontiers in Microbiology. Frontiers, Lausanne, SWITZERLAND, 11: 2254-2267, (2020).

PS_GenBank.fasta file contain the sequences of the bacterial 16S rRNA-encoding gene for each representative sequence. The sequence containing four hypervariable regions was amplified using the primer set Eub-8f and 787. PS_GenBank.xlsx file contains rows as sample and columns as entries representing the accession number (NCBI) deposited in GenBank for each representative sequence (i.e. unique sequences). PS_OTU.fasta file contain the sequences of the bacterial 16S rRNA-encoding gene for each Operational Taxonomic Unit (OTU). The sequence containing four hypervariable regions was amplified using the primer set Eub-8f and 787. This dataset is associated with the following publication: Revetta , R., V. Gomez-Alvarez, T. Gerke, J. Santodomingo , and N. Ashbolt. CHANGES IN BACTERIAL COMPOSITION OF BIOFILM IN A METROPOLITAN DRINKING WATER DISTRIBUTION SYSTEM. JOURNAL OF APPLIED MICROBIOLOGY. Blackwell Publishing, Malden, MA, USA, 121(1): 294-305, (2016).

The fasta file (BM_OTU.fasta) contain the sequences of the bacterial 16S rRNA-encoding V4 region gene (≈250 nt) for each Operational Taxonomic Unit (OTU). This dataset is associated with the following publication: Gomez-Alvarez, V., and R. Revetta. Monitoring of Nitrification in Chloraminated Drinking Water Distribution Systems With Microbiome Bioindicators Using Supervised Machine Learning. Frontiers in Microbiology. Frontiers, Lausanne, SWITZERLAND, 11: 2254-2267, (2020).

OTU sequence reads by sample, along with assigned taxonomy. This dataset is associated with the following publication: Bagley, M., E. Pilgrim, M. Knapp, C. Yoder, J. Santodomingo, and A. Banerji. High-throughput environmental DNA analysis informs a biological assessment of an urban stream. ECOLOGICAL INDICATORS. Elsevier Science Ltd, New York, NY, USA, 104: 378-389, (2019).

The U.S. Geological Survey (USGS), in cooperation with the Missouri Department of Natural Resources (MDNR), collects data pertaining to the surface-water resources of Missouri. These data are collected as part of the Missouri Ambient Water-Quality Monitoring Network (AWQMN) and are stored and maintained by the USGS National Water Information System (NWIS) database. These data constitute a valuable source of reliable, impartial, and timely information for developing an improved understanding of the water resources of the State. Water-quality data collected between 1993 and 2017 were analyzed for long term trends and the network was investigated to identify data gaps or redundant data to assist MDNR on how to optimize the network in the future. This is a companion data release product to the Scientific Investigation Report: Richards, J.M., and Barr, M.N., 2021, General water-quality conditions, long-term trends, and network analysis at selected sites within the Ambient Water-Quality Monitoring Network in Missouri, water years 1993–2017: U.S. Geological Survey Scientific Investigations Report 2021–5079, 75 p., https://doi.org/10.3133/sir20215079. The following selected tables are included in this data release in compressed (.zip) format: AWQMN_EGRET_data.xlsx -- Data retrieved from the USGS National Water Information System database that was quality assured and conditioned for network analysis of the Missouri AWQMN AWQMN_R-QWTREND_data.xlsx -- Data retrieved from the USGS National Water Information System database that was quality assured and conditioned for analysis of flow-weighted trends for selected sites in the Missouri AWQMN AWQMN_R-QWTREND_outliers.xlsx -- Data flagged as outliers during analysis of flow-weighted trends for selected sites in the Missouri AWQMN AWQMN_R-QWTREND_outliers_quarterly.xlsx -- Data flagged as outliers during analysis of flow-weighted trends using a simulated quarterly sampling frequency dataset for selected sites in the Missouri AWQMN AWQMN_descriptive_statistics_WY1993-2017.xlsx -- Descriptive statistics for selected water-quality parameters at selected sites in the Missouri AWQMN

The U.S. Geological Survey (USGS), in cooperation with the Missouri Department of Natural Resources (MDNR), collects data pertaining to the surface-water resources of Missouri. These data are collected as part of the Missouri Ambient Water-Quality Monitoring Network (AWQMN) and are stored and maintained by the USGS National Water Information System (NWIS) database. These data constitute a valuable source of reliable, impartial, and timely information for developing an improved understanding of the water resources of the State. Water-quality data collected between 1993 and 2017 were analyzed for long term trends and the network was investigated to identify data gaps or redundant data to assist MDNR on how to optimize the network in the future. This is a companion data release product to the Scientific Investigation Report: Richards, J.M., and Barr, M.N., 2021, General water-quality conditions, long-term trends, and network analysis at selected sites within the Ambient Water-Quality Monitoring Network in Missouri, water years 1993–2017: U.S. Geological Survey Scientific Investigations Report 2021–5079, 75 p., https://doi.org/10.3133/sir20215079. The following selected tables are included in this data release in compressed (.zip) format: AWQMN_EGRET_data.xlsx -- Data retrieved from the USGS National Water Information System database that was quality assured and conditioned for network analysis of the Missouri AWQMN AWQMN_R-QWTREND_data.xlsx -- Data retrieved from the USGS National Water Information System database that was quality assured and conditioned for analysis of flow-weighted trends for selected sites in the Missouri AWQMN AWQMN_R-QWTREND_outliers.xlsx -- Data flagged as outliers during analysis of flow-weighted trends for selected sites in the Missouri AWQMN AWQMN_R-QWTREND_outliers_quarterly.xlsx -- Data flagged as outliers during analysis of flow-weighted trends using a simulated quarterly sampling frequency dataset for selected sites in the Missouri AWQMN AWQMN_descriptive_statistics_WY1993-2017.xlsx -- Descriptive statistics for selected water-quality parameters at selected sites in the Missouri AWQMN