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Concentration-response Modeling in High-throughput Transcriptomics
Citation:
Judson, R., I. Shah, L. Everett, D. Haggard, B. Vallanat, J. Bundy, B. Chambers, Woodrow Setzer, AND J. Harrill. Concentration-response Modeling in High-throughput Transcriptomics. Society for Risk Analysis Dose Response Specialty Group (DRSG) teleseminar, NA, NC, May 05, 2020. https://doi.org/10.23645/epacomptox.12245897
Impact/Purpose:
Presentation to the Society for Risk Analysis Dose Response Specialty Group (DRSG) on May 5, 2020
Description:
With new lower-cost sequencing-based transcriptomics methods becoming widely available, it is now possible to run hundreds to thousands of chemicals in concentration-response mode. These large data sets bring new challenges, including how to detect and filter for various types of noise, how to group responses of probes and genes into higher level groups such as signatures and pathways, how to carry out concentration-response modeling, and finally how to visualize and analyze the final results. This presentation will describe a set of linked processes taking high-throughput transcriptomics (HTTr) data from raw reads to final analyses. Three main processing pipelines will be described: (1) raw reads to normalizes counts (sample x probe); (2) conversion of counts to fold-change values; and (3) grouping probes into gene sets or signatures and performing concentration-response modeling. All of the software for performing these steps are open sources, and examples of using the process will be given. This abstract does not necessarily reflect U.S. EPA policy.
URLs/Downloads:
DOI: Concentration-response Modeling in High-throughput Transcriptomics
DRSG HTTR JUDSON MAY 2020 V1.PDF (PDF, NA pp, 1795.741 KB, about PDF)