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Virginia Commonwealth University

1. Drake, John E, Jr. Evaluating PrediXcan’s Ability to Predict Differential Expression Between Alcoholics and Non-Alcoholics.

Degree: MS, Bioinformatics, 2019, Virginia Commonwealth University

URL: https://scholarscompass.vcu.edu/etd/5797 

PrediXcan is a recent software for the imputation of gene expression from genotype data alone. Using an overlapping set of transcriptome datasets from postmortem brain tissues of donors with alcohol use disorder and neurotypical controls, which were generated by two different platforms (e.g., Arraystar and Affymetrix), and an additional unrelated transcriptome dataset from lung tissue, we sought to evaluate PrediXcan’s ability to impute gene expression and identify differentially expressed genes. From the Arraystar platform, 1.3% of matched genes between the measured and imputed expression had a Pearson correlation ≥ 0.5. Our attempt to replicate this finding using the expression data from the Affymetrix platform also lead to a similarly poor outcome (2.7%). Our third attempt using the transcriptome data from lung tissue produced similar results (1.1%) but performance improved markedly after filtering out genes with a low predicted R2, which was a model metric provided by the PrediXcan authors. For example, filtering out genes with a predicted R2 below 0.6 led to 16 genes remaining and a Pearson correlation of 0.365 between the measured and imputed expression. We were unable to reproduce similar performance gains with filtering the Arraystar or Affymetrix alcohol use disorder datasets. Given that PrediXcan can impute a narrow portion of the transcriptome, which is further reduced significantly by filtering, we believe caution is warranted with the interpretation of results derived from PrediXcan. Advisors/Committee Members: Vladimir Vladimirov.

Subjects/Keywords: PrediXcan; bioinformatics; limma; alcoholism; imputation; Bioinformatics

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APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Drake, John E, J. (2019). Evaluating PrediXcan’s Ability to Predict Differential Expression Between Alcoholics and Non-Alcoholics. (Thesis). Virginia Commonwealth University. Retrieved from https://scholarscompass.vcu.edu/etd/5797

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Chicago Manual of Style (16th Edition):

Drake, John E, Jr. “Evaluating PrediXcan’s Ability to Predict Differential Expression Between Alcoholics and Non-Alcoholics.” 2019. Thesis, Virginia Commonwealth University. Accessed December 08, 2019. https://scholarscompass.vcu.edu/etd/5797.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

MLA Handbook (7th Edition):

Drake, John E, Jr. “Evaluating PrediXcan’s Ability to Predict Differential Expression Between Alcoholics and Non-Alcoholics.” 2019. Web. 08 Dec 2019.

Vancouver:

Drake, John E J. Evaluating PrediXcan’s Ability to Predict Differential Expression Between Alcoholics and Non-Alcoholics. [Internet] [Thesis]. Virginia Commonwealth University; 2019. [cited 2019 Dec 08]. Available from: https://scholarscompass.vcu.edu/etd/5797.

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

Council of Science Editors:

Drake, John E J. Evaluating PrediXcan’s Ability to Predict Differential Expression Between Alcoholics and Non-Alcoholics. [Thesis]. Virginia Commonwealth University; 2019. Available from: https://scholarscompass.vcu.edu/etd/5797

Note: this citation may be lacking information needed for this citation format:
Not specified: Masters Thesis or Doctoral Dissertation

2. Ferreira Filho, Diógenes. Estudo de expressão gênica em citros utilizando modelos lineares.

Degree: Mestrado, Estatística e Experimentação Agronômica, 2010, University of São Paulo

URL: http://www.teses.usp.br/teses/disponiveis/11/11134/tde-16032010-111945/  ;

Neste trabalho apresenta-se uma revisão da metodologia de experimentos de microarray relativas a sua instalação e análise estatística dos dados obtidos. A seguir, aplica-se essa metodologia na análise de dados de expressão gênica em citros, gerados por um experimento de macroarray, utilizando modelos lineares de efeitos fixos considerando a inclusão ou não de diferentes efeitos e considerando ajustes de modelos para cada gene separadamente e para todos os genes simultaneamente. Os experimentos de macroarray são similares aos experimentos de microarray, porém utilizam um menor número de genes. Em geral, são utilizados devido a restrições econômicas. Devido ao fato de terem sido utilizados poucos arrays no experimento analisado neste trabalho foi utilizada uma abordagem bayesiana empírica que utiliza estimativas de variância mais estáveis e que leva em consideração a correlação entre as repetições do gene dentro do array. Também foi utilizado um método de análise não paramétrico para contornar o problema da falta de normalidade para alguns genes. Os resultados obtidos em cada um dos métodos de análise descritos foram então comparados.

This paper presents a review of the methodology of microarray experiments for its installation and statistical analysis of data obtained. Then this methodology is applied in data analysis of gene expression in citrus, generated by a macroarray experiment, using linear models with fixed effects considering the inclusion or exclusion of different effects and considering adjustments of models for each gene separately and for all genes simultaneously. The macroarray experiments are similar to the microarray experiments, but use a smaller number of genes. In general, are used due to economic restrictions. Because they have been used a few arrays in the experiment analyzed in this study it was used a empirical Bayes approach that uses estimates of variance more stable and that takes into account the correlation among replicates of the gene within array. A non parametric analysis method was also used to outline the problem of the non normality for some genes. The results obtained in each of the described methods of analysis were then compared.

Advisors/Committee Members: Leandro, Roseli Aparecida.

Subjects/Keywords: Bioconductor; Citrus; DNA - Análise; empirical Bayes method; Expressão gênica; FDR; fixed linear model; Frutas cítricas - Experimentos; Inferência bayesiana; Limma package.; Macroarray; Microarray; Modelos lineares.; software R

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❌

APA · Chicago · MLA · Vancouver · CSE | Export to Zotero / EndNote / Reference Manager

APA (6th Edition):

Ferreira Filho, D. (2010). Estudo de expressão gênica em citros utilizando modelos lineares. (Masters Thesis). University of São Paulo. Retrieved from http://www.teses.usp.br/teses/disponiveis/11/11134/tde-16032010-111945/ ;

Chicago Manual of Style (16th Edition):

Ferreira Filho, Diógenes. “Estudo de expressão gênica em citros utilizando modelos lineares.” 2010. Masters Thesis, University of São Paulo. Accessed December 08, 2019. http://www.teses.usp.br/teses/disponiveis/11/11134/tde-16032010-111945/ ;.

MLA Handbook (7th Edition):

Ferreira Filho, Diógenes. “Estudo de expressão gênica em citros utilizando modelos lineares.” 2010. Web. 08 Dec 2019.

Vancouver:

Ferreira Filho D. Estudo de expressão gênica em citros utilizando modelos lineares. [Internet] [Masters thesis]. University of São Paulo; 2010. [cited 2019 Dec 08]. Available from: http://www.teses.usp.br/teses/disponiveis/11/11134/tde-16032010-111945/ ;.

Council of Science Editors:

Ferreira Filho D. Estudo de expressão gênica em citros utilizando modelos lineares. [Masters Thesis]. University of São Paulo; 2010. Available from: http://www.teses.usp.br/teses/disponiveis/11/11134/tde-16032010-111945/ ;

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