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1.
Bioinformatics ; 39(5)2023 05 04.
Article in English | MEDLINE | ID: mdl-37140544

ABSTRACT

MOTIVATION: The identification of differentially expressed genes (DEGs) from transcriptomic datasets is a major avenue of research across diverse disciplines. However, current bioinformatic tools do not support covariance matrices in DEG modeling. Here, we introduce kimma (Kinship In Mixed Model Analysis), an open-source R package for flexible linear mixed effects modeling including covariates, weights, random effects, covariance matrices, and fit metrics. RESULTS: In simulated datasets, kimma detects DEGs with similar specificity, sensitivity, and computational time as limma unpaired and dream paired models. Unlike other software, kimma supports covariance matrices as well as fit metrics like Akaike information criterion (AIC). Utilizing genetic kinship covariance, kimma revealed that kinship impacts model fit and DEG detection in a related cohort. Thus, kimma equals or outcompetes current DEG pipelines in sensitivity, computational time, and model complexity. AVAILABILITY AND IMPLEMENTATION: Kimma is freely available on GitHub https://github.com/BIGslu/kimma with an instructional vignette at https://bigslu.github.io/kimma_vignette/kimma_vignette.html.


Subject(s)
Gene Expression Profiling , Software , Humans , RNA-Seq , Sequence Analysis, RNA , Linear Models
2.
Environ Sci Pollut Res Int ; 29(21): 31059-31074, 2022 May.
Article in English | MEDLINE | ID: mdl-34686963

ABSTRACT

Despite significant investigation of fly ash spills and mineralogical controls on the release of potentially toxic elements (PTEs) from fly ash, interactions with the surficial environment remain relatively poorly understood. We conducted 90-day batch leaching studies with paired analysis of supernatant and solid-phase mineralogy to assess the elemental release and transformation of fly ash upon reaction with aquatic media (18 MΩ cm-1 water and simulated rainwater). The fly ash in this study, collected from the University of Alaska Fairbanks stoker-boiler power plant, is high in unburned carbon (~20% LOI) and highly enriched in several PTEs relative to the upper continental crust. Supernatant concentrations of oxyanion-forming elements (e.g., As, Se, Mo, Sb) remained relatively low and constant, suggesting equilibrium with the solid phase, possibly ettringite [Ca6Al2(SO4)3(OH)12•26H2O], which is known to incorporate and sorb oxyanion-forming PTEs and was identified by X-ray diffraction. Synthetic precipitation leaching procedure (SPLP) results failed to capture important temporal trends. Lead and Ba supernatant concentrations consistently exceeded drinking water standards, as well as others upon exposure to simulated physiological solutions. Seven-day experiments with dissolved organic matter-isolate solutions indicated that for certain elements, liberation was influenced by carbon concentration and/or the identity of the isolate. Overall, this paired approach can serve as a model for future studies, bridging existing gaps between batch leaching and single-element mineralogical, sorption, or speciation studies.


Subject(s)
Coal Ash , Power Plants , Alaska , Carbon , X-Ray Diffraction
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