Statistical analysis of real-time PCR data

BACKGROUND: Even though real-time PCR has been broadly applied in biomedical sciences, data processing procedures for the analysis of quantitative real-time PCR are still lacking; specifically in the realm of appropriate statistical treatment. Confidence interval and statistical significance considerations are not explicit in many of the current data analysis approaches. Based on the standard curve method and other useful data analysis methods, we present and compare four statistical approaches and models for the analysis of real-time PCR data. RESULTS: In the first approach, a multiple regression analysis model was developed to derive ΔΔCt from estimation of interaction of gene and treatment effects. In the second approach, an ANCOVA (analysis of covariance) model was proposed, and the ΔΔCt can be derived from analysis of effects of variables. The other two models involve calculation ΔCt followed by a two group t-test and non-parametric analogous Wilcoxon test. SAS programs were developed for all four models and data output for analysis of a sample set are presented. In addition, a data quality control model was developed and implemented using SAS. CONCLUSION: Practical statistical solutions with SAS programs were developed for real-time PCR data and a sample dataset was analyzed with the SAS programs. The analysis using the various models and programs yielded similar results. Data quality control and analysis procedures presented here provide statistical elements for the estimation of the relative expression of genes using real-time PCR

Dynamical masses across the Hertzsprung-Russell diagram

We infer the dynamical masses of stars across the Hertzsprung-Russell (H-R) diagram using wide binaries from the Gaia survey. Gaia's high-precision astrometry measures the wide binaries' orbital motion, which contains the mass information. Using wide binaries as the training sample, we measure the mass of stars across the two-dimensional H-R diagram using the combination of statistical inference and neural networks. Our results provide the dynamical mass measurements for main-sequence stars from 0.1 to 2 M$_\odot$, unresolved binaries and unresolved triples on the main sequence, and the mean masses of giants and white dwarfs. Two regions in the H-R diagram show interesting behaviors in mass, where one of them is pre-main-sequence stars, and the other one may be related to close compact object companions like M dwarf-white dwarf binaries. These mass measurements depend solely on Newtonian dynamics, providing independent constraints on stellar evolutionary models and the occurrence rate of compact objects.Comment: Fig. 5 and Fig. 12 are the key results. Submitted to MNRAS. Comments are welcome

Zephyr : Stitching Heterogeneous Training Data with Normalizing Flows for Photometric Redshift Inference

We present zephyr, a novel method that integrates cutting-edge normalizing flow techniques into a mixture density estimation framework, enabling the effective use of heterogeneous training data for photometric redshift inference. Compared to previous methods, zephyr demonstrates enhanced robustness for both point estimation and distribution reconstruction by leveraging normalizing flows for density estimation and incorporating careful uncertainty quantification. Moreover, zephyr offers unique interpretability by explicitly disentangling contributions from multi-source training data, which can facilitate future weak lensing analysis by providing an additional quality assessment. As probabilistic generative deep learning techniques gain increasing prominence in astronomy, zephyr should become an inspiration for handling heterogeneous training data while remaining interpretable and robustly accounting for observational uncertainties.Comment: 10 pages, 5 figures, accepted to NeurIPS 2023 workshop on Machine Learning and the Physical Science

Comparative genomic analysis of NAC transcriptional factors to dissect the regulatory mechanisms for cell wall biosynthesis

BACKGROUND: NAC domain transcription factors are important transcriptional regulators involved in plant growth, development and stress responses. Recent studies have revealed several classes of NAC transcriptional factors crucial for controlling secondary cell wall biosynthesis. These transcriptional factors mainly include three classes, SND, NST and VND. Despite progress, most current analysis is carried out in the model plant Arabidopsis. Moreover, many downstream genes regulated by these transcriptional factors are still not clear. METHODS: In order to identify the key homologue genes across species and discover the network controlling cell wall biosynthesis, we carried out comparative genome analysis of NST, VND and SND genes across 19 higher plant species along with computational modelling of genes regulated or co-regulated with these transcriptional factors. RESULTS: The comparative genome analysis revealed that evolutionarily the secondary-wall-associated NAC domain transcription factors first appeared in Selaginella moellendorffii. In fact, among the three groups, only VND genes appeared in S. moellendorffii, which is evolutionarily earlier than the other two groups. The Arabidopsis and rice gene expression analysis showed specific patterns of the secondary cell wall-associated NAC genes (SND, NST and VND). Most of them were preferentially expressed in the stem, especially the second internodes. Furthermore, comprehensive co-regulatory network analysis revealed that the SND and MYB genes were co-regulated, which indicated the coordinative function of these transcriptional factors in modulating cell wall biosynthesis. In addition, the co-regulatory network analysis revealed many novel genes and pathways that could be involved in cell wall biosynthesis and its regulation. The gene ontology analysis also indicated that processes like carbohydrate synthesis, transport and stress response, are coordinately regulated toward cell wall biosynthesis. CONCLUSIONS: Overall, we provided a new insight into the evolution and the gene regulatory network of a subgroup of the NAC gene family controlling cell wall composition through bioinformatics data mining and bench validation. Our work might benefit to elucidate the possible molecular mechanism underlying the regulation network of secondary cell wall biosynthesis

Statistical tools for transgene copy number estimation based on real-time PCR

Background As compared with traditional transgene copy number detection technologies such as Southern blot analysis, real-time PCR provides a fast, inexpensive and high-throughput alternative. However, the real-time PCR based transgene copy number estimation tends to be ambiguous and subjective stemming from the lack of proper statistical analysis and data quality control to render a reliable estimation of copy number with a prediction value. Despite the recent progresses in statistical analysis of real-time PCR, few publications have integrated these advancements in real-time PCR based transgene copy number determination. Results Three experimental designs and four data quality control integrated statistical models are presented. For the first method, external calibration curves are established for the transgene based on serially-diluted templates. The Ct number from a control transgenic event and putative transgenic event are compared to derive the transgene copy number or zygosity estimation. Simple linear regression and two group T-test procedures were combined to model the data from this design. For the second experimental design, standard curves were generated for both an internal reference gene and the transgene, and the copy number of transgene was compared with that of internal reference gene. Multiple regression models and ANOVA models can be employed to analyze the data and perform quality control for this approach. In the third experimental design, transgene copy number is compared with reference gene without a standard curve, but rather, is based directly on fluorescence data. Two different multiple regression models were proposed to analyze the data based on two different approaches of amplification efficiency integration. Our results highlight the importance of proper statistical treatment and quality control integration in real-time PCR-based transgene copy number determination. Conclusion These statistical methods allow the real-time PCR-based transgene copy number estimation to be more reliable and precise with a proper statistical estimation. Proper confidence intervals are necessary for unambiguous prediction of trangene copy number. The four different statistical methods are compared for their advantages and disadvantages. Moreover, the statistical methods can also be applied for other real-time PCR-based quantification assays including transfection efficiency analysis and pathogen quantification

The Effects of an Obesogenic Diet on Liver Oxysterol Metabolism in C57BL/6J Mice

Oxysterols are key regulators of lipid metabolism and play a role in the etiology of atherosclerosis; however, our current understanding of tissue levels of oxysterols during different disease states such as obesity is limited. The purpose of this study was to quantify the effects of obesity induced by a high fat-cholesterol (HFC) diet on liver oxysterol metabolism. Male C57BL/6J mice were fed either a standard control diet (5.0% w/w fat, 0.03% w/w chol) or a HFC (21.0% w/w fat, 0.15% w/w chol) diet for 24 weeks. Comparisons between dietary groups were made with independent sample t-tests. Total body mass and liver tissue mass of the HFC group was greater (33.2±5.2 vs. 49.0±3.6 g and 1.4±0.3 vs. 3.9±0.8 g, respectively; P\u3c0.05) than the control group. In the HFC group, a 3.3 fold increase in lipid mass of the liver tissue was due to increased levels of cholesterol (0.10±0.01 vs. 0.33±0.06 mg/mg protein; P\u3c0.05) and triglyceride (0.37±0.05 vs. 1.49±0.12 mg/mg protein; P\u3c0.05). In the HFC diet, 4β-OH, 5,6β-epoxy, and 27-OH were greater and 7-keto was lower when compared to the control diet. Post-dietary liver 4β-OH, 5,6β-epoxy, and 27-OH were increased in the HFC diet group. Interestingly, despite increased oxysterol levels no significant changes in mRNA levels were observed for oxysterol-related enzymes CYP3A11, CYP27A1 or CYP7A1. The 24-week HFC diet was effective at promoting obesity and hepatic steatosis in mice. Due to the low concentration of oxysterols in the diet, it is unlikely that the oxysterols in the diet had a significant impact on liver oxysterols. Furthermore, our results suggest that the increased hepatic oxysterol levels observed in mice on the obesogenic diet were not due to increased rates of oxysterol synthesis

MINESweeper: Spectrophotometric Modeling of Stars in the Gaia Era

We present MINESweeper, a tool to measure stellar parameters by jointly fitting observed spectra and broadband photometry to model isochrones and spectral libraries. This approach enables the measurement of spectrophotometric distances, in addition to stellar parameters such as Teff, log(g), [Fe/H], [a/Fe], and radial velocity. MINESweeper employs a Bayesian framework and can easily incorporate a variety of priors, including Gaia parallaxes. Mock data are fit in order to demonstrate how the precision of derived parameters depends on evolutionary phase and SNR. We then fit a selection of data in order to validate the model outputs. Fits to a variety of benchmark stars including Procyon, Arcturus, and the Sun result in derived stellar parameters that are in good agreement with the literature. We then fit combined spectra and photometry of stars in the open and globular clusters M92, M13, M3, M107, M71, and M67. Derived distances, [Fe/H], [a/Fe], and log(g)-Teff, relations are in overall good agreement with literature values, although there are trends between metallicity and log(g), within clusters that point to systematic uncertainties at the ~0.1 dex level. Finally, we fit a large sample of stars from the H3 Spectroscopic Survey in which high quality Gaia parallaxes are also available. These stars are fit without the Gaia parallaxes so that the geometric parallaxes can serve as an independent test of the spectrophotometric distances. Comparison between the two reveals good agreement within their formal uncertainties after accounting for the Gaia zero point uncertainties.Comment: 20 pages, 14 figures, Accepted by Ap