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Full-Text Articles in Bioinformatics
Risk Prediction With Genomic Data, Bharati Jadhav
Risk Prediction With Genomic Data, Bharati Jadhav
Theses
Genome wide association study (GWAS) is widely used with various machine learning algorithms to predict disease risk. This thesis investigates this widely used approach of GWAS using Single Nucleotide Polymorphism (SNP) genotype data and a novel approach of disease risk prediction with whole exome sequencing data, namely Whole Exome Wide Association Study (WEWAS). It further applies a discriminating machine learning algorithm, namely a Support Vector Machine (SVM) with different Kernel functions. For this study, only SNPs generated using genotyping technology, which focuses more on common variants, are used initially for disease prediction. Later, the whole exome data generated using Next …
Comparison Of Different Differential Expression Analysis Tools For Rna-Seq Data, Junfei Zhu
Comparison Of Different Differential Expression Analysis Tools For Rna-Seq Data, Junfei Zhu
Theses
In molecular biology research, RNA-seq is a relatively new method for transcriptome profiling. It utilizes the next generation sequencing technology to provide huge amount information about the variety and abundance of RNA present in an organism of interest at a specific state and a given time. One of the most important tasks of RNA-seq analysis is finding genes that are expressed differently in different subject groups. A lot of differential expression analysis tools for RNA-seq have been developed, but there is no golden standard in this field. In this research, four commonly used tools (DESeq, edgeR, limma, and cuffdiff) are …