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Biomedical subjects

Gregory R Grant

Publications and source records attributed to Gregory R Grant.

12 recordsLinked to original sources
PubMed2026

MAJIQ-CLIN: A novel tool to help identify Mendelian disease-causing variants from RNA-seq data.

PURPOSE: The current diagnostic rate for patients with suspected Mendelian genetic disorders is low, despite exome/genome sequencing being the standard of care. One reason for this low diagnostic rate is that traditional exome/genome sequencing analysis methods struggle to detect RNA splicing aberrations. Causative variants often involve splicing changes, with numerous splice-altering variants being responsible for known Mendelian disorders. Therefore, it is crucial to develop reliable tools to detect, quantify, prioritize, and visualize RNA splicing aberrations from patient RNA sequencing data. METHODS: We developed Modeling Alternative Junction Inclusion Quantification for Clinical Applications (MAJIQ-CLIN), a method to identify RNA splicing aberrations in patients' RNA sequencing data compared with a cohort of control samples. MAJIQ-CLIN can efficiently process large datasets, avoiding reprocessing when new data are added, while effectively detecting local splicing variations with deviations in a given patient, termed outlier local splicing variation, or unique to the patient, termed private local splicing variation. RESULTS: We performed a systematic evaluation of the accuracy of tools for detecting patients' RNA splicing aberrations from RNA sequence using synthetic data across several aberration types and transcript inclusion levels. Then, we used several real datasets to assess MAJIQ-CLINs ability to identify solved test cases and control for the effect of confounders such as batches. We showed that MAJIQ-CLIN compares favorably to existing tools in both accuracy and efficiency. We also used MAJIQ-CLIN to investigate several unsolved patient cases from the Undiagnosed Diseases Network. CONCLUSION: MAJIQ-CLIN offers an efficient, accurate, and user-friendly tool to aid in diagnosing Mendelian disease-causing variants from RNA sequence data.

Bioinformatics↗
PubMed2025

Generating correlated data for omics simulation.

Simulation of realistic omics data is a key input for benchmarking studies that help users obtain optimal computational pipelines. Omics data involves large numbers of measured features on each sample and these measures are generally correlated with each other. However, simulation too often ignores these correlations, perhaps due to computational and statistical hurdles of doing so. To alleviate this, we describe three approaches for generating omics-scale data with correlated measures which mimic real datasets. These approaches are all based on a Gaussian copula approach with a covariance matrix that decomposes into a diagonal part and a low-rank part. This decomposition allows for extremely efficient simulation, overcoming a hurdle for adoption of past methods. We use these approaches to demonstrate the importance of including correlation in two benchmarking applications. First, we show that variance of results from the popular DESeq2 method increases when dependence is included. Second, we demonstrate that CYCLOPS, a method for inferring circadian time of collection from transcriptomics, improves in performance when given gene-gene dependencies in some circumstances. We provide an R package, dependentsimr, that has efficient implementations of these methods and can generate dependent data with arbitrary marginal distributions, including discrete (binary, ordered categorical, Poisson, negative binomial), continuous (normal), or with an empirical distribution.

Computer Simulation↗
PubMed2006

STAC: A method for testing the significance of DNA copy number aberrations across multiple array-CGH experiments.

Regions of gain and loss of genomic DNA occur in many cancers and can drive the genesis and progression of disease. These copy number aberrations (CNAs) can be detected at high resolution by using microarray-based techniques. However, robust statistical approaches are needed to identify nonrandom gains and losses across multiple experiments/samples. We have developed a method called Significance Testing for Aberrant Copy number (STAC) to address this need. STAC utilizes two complementary statistics in combination with a novel search strategy. The significance of both statistics is assessed, and P-values are assigned to each location on the genome by using a multiple testing corrected permutation approach. We validate our method by using two published cancer data sets. STAC identifies genomic alterations known to be of clinical and biological significance and provides statistical support for 85% of previously reported regions. Moreover, STAC identifies numerous additional regions of significant gain/loss in these data that warrant further investigation. The P-values provided by STAC can be used to prioritize regions for follow-up study in an unbiased fashion. We conclude that STAC is a powerful tool for identifying nonrandom genomic amplifications and deletions across multiple experiments. A Java version of STAC is freely available for download at http://cbil.upenn.edu/STAC.

Algorithms↗
PubMed2005

Regional determinants of arterial endothelial phenotype dominate the impact of gender or short-term exposure to a high-fat diet.

Regional arterial hemodynamics correlates with distinct endothelial phenotypes that may be modified by risk factors to influence focal and regional susceptibility to atherosclerosis. We compared endothelial transcript profiles from hemodynamically distinct arterial regions in 15 mature pigs: males and females fed a normal diet, and males fed a high-fat diet (15% lard, 1.5% cholesterol) for two weeks. Hierarchical clustering analysis showed preferential grouping of arrays by region over risk factor. A set of differentially expressed genes was identified which clearly distinguished regions of disturbed flow from undisturbed flow; however, few differences were observed within the same region based on gender or diet. Consistent with previous results in the absence of risk factors, the balance in gene expression was not inherently pathological at this early time-point. The results implicate regional hemodynamics as a predominant epigenetic determinant of endothelial phenotypic heterogeneity underlying atherosusceptibility in vivo.

Animals↗
PubMed2005

A practical false discovery rate approach to identifying patterns of differential expression in microarray data.

SUMMARY: Searching for differentially expressed genes is one of the most common applications for microarrays, yet statistically there are difficult hurdles to achieving adequate rigor and practicality. False discovery rate (FDR) approaches have become relatively standard; however, how to define and control the FDR has been hotly debated. Permutation estimation approaches such as SAM and PaGE can be effective; however, they leave much room for improvement. We pursue the permutation estimation method and describe a convenient definition for the FDR that can be estimated in a straightforward manner. We then discuss issues regarding the choice of statistic and data transformation. It is impossible to optimize the power of any statistic for thousands of genes simultaneously, and we look at the practical consequences of this. For example, the log transform can both help and hurt at the same time, depending on the gene. We examine issues surrounding the SAM 'fudge factor' parameter, and how to handle these issues by optimizing with respect to power.

Algorithms↗
PubMed2005

Spatial heterogeneity of endothelial phenotypes correlates with side-specific vulnerability to calcification in normal porcine aortic valves.

Calcific aortic valve sclerosis involves inflammatory processes and occurs preferentially on the aortic side of endothelialized valve leaflets. Although the endothelium is recognized to play critical roles in focal vascular sclerosis, the contributions of valvular endothelial phenotypes to aortic valve sclerosis and side-specific susceptibility to calcification are poorly understood. Using RNA amplification and cDNA microarrays, we identified 584 genes as differentially expressed in situ by the endothelium on the aortic side versus ventricular side of normal adult pig aortic valves. These differential transcriptional profiles, representative of the steady state in vivo, identify globally distinct endothelial phenotypes on opposite sides of the aortic valve. Several over-represented biological classifications with putative relevance to endothelial regulation of valvular homeostasis and aortic-side vulnerability to calcification were identified among the differentially expressed genes. Of note, multiple inhibitors of cardiovascular calcification were significantly less expressed by endothelium on the disease-prone aortic side of the valve, suggesting side-specific permissiveness to calcification. However, coexisting putative protective mechanisms were also expressed. Specifically, enhanced antioxidative gene expression and the lack of differential expression of proinflammatory molecules on the aortic side may protect against inflammation and lesion initiation in the normal valve. These data implicate the endothelium in regulating valvular calcification and suggest that spatial heterogeneity of valvular endothelial phenotypes may contribute to the focal susceptibility for lesion development.

Animals↗
PubMed2004

Coexisting proinflammatory and antioxidative endothelial transcription profiles in a disturbed flow region of the adult porcine aorta.

In the arterial circulation, regions of disturbed flow (DF), which are characterized by flow separation and transient vortices, are susceptible to atherogenesis, whereas regions of undisturbed laminar flow (UF) appear protected. Coordinated regulation of gene expression by endothelial cells (EC) may result in differing regional phenotypes that either favor or inhibit atherogenesis. Linearly amplified RNA from freshly isolated EC of DF (inner aortic arch) and UF (descending thoracic aorta) regions of normal adult pigs was used to profile differential gene expression reflecting the steady state in vivo. By using human cDNA arrays, approximately 2,000 putatively differentially expressed genes were identified through false-discovery-rate statistical methods. A sampling of these genes was validated by quantitative real-time PCR and/or immunostaining en face. Biological pathway analysis revealed that in DF there was up-regulation of several broad-acting inflammatory cytokines and receptors, in addition to elements of the NF-kappaB system, which is consistent with a proinflammatory phenotype. However, the NF-kappaB complex was predominantly cytoplasmic (inactive) in both regions, and no significant differences were observed in the expression of key adhesion molecules for inflammatory cells associated with early atherogenesis. Furthermore, there was no histological evidence of inflammation. Protective profiles were observed in DF regions, notably an enhanced antioxidative gene expression. This study provides a public database of regional EC gene expression in a normal animal, implicates hemodynamics as a contributory mechanism to athero-susceptibility, and reveals the coexistence of pro- and antiatherosclerotic transcript profiles in susceptible regions. The introduction of additional risk factors may shift this balance to favor lesion development.

Animals↗
PubMed2003

Fidelity and enhanced sensitivity of differential transcription profiles following linear amplification of nanogram amounts of endothelial mRNA.

Although mRNA amplification is necessary for microarray analyses from limited amounts of cells and tissues, the accuracy of transcription profiles following amplification has not been well characterized. We tested the fidelity of differential gene expression following linear amplification by T7-mediated transcription in a well-established in vitro model of cytokine [tumor necrosis factor alpha (TNFalpha)]-stimulated human endothelial cells using filter arrays of 13,824 human cDNAs. Transcriptional profiles generated from amplified antisense RNA (aRNA) (from 100 ng total RNA, approximately 1 ng mRNA) were compared with profiles generated from unamplified RNA originating from the same homogeneous pool. Amplification accurately identified TNFalpha-induced differential expression in 94% of the genes detected using unamplified samples. Furthermore, an additional 1,150 genes were identified as putatively differentially expressed using amplified RNA which remained undetected using unamplified RNA. Of genes sampled from this set, 67% were validated by quantitative real-time PCR as truly differentially expressed. Thus, in addition to demonstrating fidelity in gene expression relative to unamplified samples, linear amplification results in improved sensitivity of detection and enhances the discovery potential of high-throughput screening by microarrays.

Bias↗
PubMed2003

PlasmoDB: the Plasmodium genome resource. A database integrating experimental and computational data.

PlasmoDB (http://PlasmoDB.org) is the official database of the Plasmodium falciparum genome sequencing consortium. This resource incorporates the recently completed P. falciparum genome sequence and annotation, as well as draft sequence and annotation emerging from other Plasmodium sequencing projects. PlasmoDB currently houses information from five parasite species and provides tools for intra- and inter-species comparisons. Sequence information is integrated with other genomic-scale data emerging from the Plasmodium research community, including gene expression analysis from EST, SAGE and microarray projects and proteomics studies. The relational schema used to build PlasmoDB, GUS (Genomics Unified Schema) employs a highly structured format to accommodate the diverse data types generated by sequence and expression projects. A variety of tools allow researchers to formulate complex, biologically-based, queries of the database. A stand-alone version of the database is also available on CD-ROM (P. falciparum GenePlot), facilitating access to the data in situations where internet access is difficult (e.g. by malaria researchers working in the field). The goal of PlasmoDB is to facilitate utilization of the vast quantities of genomic-scale data produced by the global malaria research community. The software used to develop PlasmoDB has been used to create a second Apicomplexan parasite genome database, ToxoDB (http://ToxoDB.org).

Animals↗
PubMed2002

Comparison of different labeling methods for two-channel high-density microarray experiments.

In this report we evaluate three methods for labeling nucleic acids to be hybridized to a cDNA microarray: direct labeling, indirect amino-allyl labeling, and the dendrimer labeling method (Genisphere). The dendrimer method requires the smallest quantity of sample, 2.5 microg of total RNA compared with 20 microg with the direct or indirect methods. Therefore, we wanted to know whether the performance of the dendrimer method is comparable to the other methods, or whether significant information is lost. Performance can be considered in terms of sensitivity, dynamic range, and reproducibility of the quantitative signals for gene intensity. We compared the three labeling methods by generating three sets of eight self-to-self hybridizations using the same total RNA sample in all cases ("replicate study"). In our analysis, we controlled for the effects of print-tip and background subtraction biases. We also performed a smaller study, namely, a dilution series study with five dilution points per labeling method, to evaluate one aspect of predictive ability. From the replicate study, the dendrimer method appeared to perform as well, and often better, with respect to reproducibility and ability to detect expression. However, in the dilution series study, this method was outperformed by the other two in terms of predictive ability and did not perform very well. These findings are helping to guide our decisions on what labeling method to use for subsequent studies, based on the purpose of a specific study and its limitations in terms of available material.

Fluorescent Dyes↗
PubMed2002

PlasmoDB: the Plasmodium genome resource. An integrated database providing tools for accessing, analyzing and mapping expression and sequence data (both finished and unfinished).

PlasmoDB (http://PlasmoDB.org) is the official database of the Plasmodium falciparum genome sequencing consortium. This resource incorporates finished and draft genome sequence data and annotation emerging from Plasmodium sequencing projects. PlasmoDB currently houses information from five parasite species and provides tools for cross-species comparisons. Sequence information is also integrated with other genomic-scale data emerging from the Plasmodium research community, including gene expression analysis from EST, SAGE and microarray projects. The relational schemas used to build PlasmoDB [Genomics Unified Schema (GUS) and RNA Abundance Database (RAD)] employ a highly structured format to accommodate the diverse data types generated by sequence and expression projects. A variety of tools allow researchers to formulate complex, biologically based queries of the database. A version of the database is also available on CD-ROM (Plasmodium GenePlot), facilitating access to the data in situations where Internet access is difficult (e.g. by malaria researchers working in the field). The goal of PlasmoDB is to enhance utilization of the vast quantities of data emerging from genome-scale projects by the global malaria research community.

Animals↗