Global ETD Search
Search theses and dissertations gathered from participating repositories worldwide. Every result links back to the library that holds it. No account is needed.
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Showing 1 to 20 of 23 for “"Batch effects"”.
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A Variational Lower Bound to Mitigate Batch Effect in Molecular Representations
… experiments, a key difficulty is dealing with batch effects, which can introduce systematic errors and non-biological associations in the data. We propose InfoCORE, an Information maximization approach for COnfounder REmoval, to effectively deal with batch effects and obtain refined molecular …
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Characterization, representation, and prediction of immune cell states using single-cell sequencing and machine learning
… sparsity, stochastic noise, and technical batch effects that can obscure underlying biological signals. Navigating this complexity necessitates the development of sophisticated computational frameworks capable of modeling of single-cell data. This dissertation presents comprehensive …
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Scalable Machine Learning Methods For The Analysis Of Single-Cell Transcriptomics And Multiomics Data
… type classification difficult. (2) Technical batch effects also often plague scRNA-seq studies and confound real biological signals. (3) Multi-modality technologies are excellent but remain expensive to do at scale. In this work, we seek to address these various challenges and difficulties …
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STATISTICAL METHODS FOR ANALYSIS OF HIGH-DIMENSIONAL NEUROIMAGING DATA
… Neuroimaging data collected from multiple batches, such as different scanners, are increasingly necessary to obtain large sample sizes and discover small effects. However, significant confounding is present in this data due to batch-induced technical variation, called batch effects. We …
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Computational methods for genomic variant calling and analysis
… Chapter Two presents a study of the impact of batch effect and study design on identification of genetic risk factors in human sequencing data. Sequencing-based searches for disease-associated variants require large sample sizes to achieve sufficient statistical power, but they often entail …
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A Framework for 3D Mouse Brain Reconstruction: RNA-based Stitching of Adjacent Tissue Slices and Co-Registration of Multimodal Imaging Data
… a cohesive 3D volume while correcting for both batch effects and inherent sample variability. This thesis presents a novel framework that addresses these challenges through three primary contributions. First, a memory-efficient, non-referenced-based algorithm was developed to align the …
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CancerSubtyper: A Web-Based Deep Learning Platform for Cancer Subtyping Through DNA Methylation Data
… remains challenging due to high dimensionality, batch effects, and lack of standardized tools. In this thesis, we present CancerSubtyper, a web-based deep learning platform that enables both supervised classification and semi-supervised discovery of cancer subtypes using methylation data. The …
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Machine learning methodologies for high dimensional biomedical & bioinformatics applications
… along with a PCA-based approach to remove study batch effects and validate our classification results. Second, we proposed to incorporate the phylogenetic information of microbes as graphs via a graphical convolutional neural network to improve the classification performances for dietary and …
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Systems approaches to identify molecular signatures from high-throughput expression data: towards next generation patient diagnostics
… diagnostic signatures and addressing of batch effects through multi-study integration of brain cancer transcriptomes; and (3) Identification of conserved expression patterns in mRNA and protein profiles from human cancers for prediction of relative feature abundances across heterogeneous …
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Cellular Kaleidoscope: Unveiling Tissue Microenvironment in Health and Disease
… robustness and accuracy in the presence of batch effects between reference and bulk data. Results show that some methods are more resilient to batch effects than others, highlighting the need to test newly developed methods under these conditions. The next chapter explores the performance of …
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Bayesian model-based clustering of multi-source data
… generated across different contexts, and multi-batch, where the same measurements are taken on sets of items. I develop and explore a consensus clustering approach to navigate the problem of poor mixing, which refers to a failure of Markov chain Monte Carlo methods wherein the sampler becomes …
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Accurate estimation of drug combination synergies with uncertainty quantification
… the predictions. We then extend SynBa to SynBa-Batch to explain away the batch effects existing in the noisy measurements so that the noise can be better understood. We provide a route for SynBa and SynBa-Batch to utilise existing monotherapy information and design more informed priors. This …
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Bioinformatics pipeline development for analyses of data generated by target capture-based Next-Generation Sequencing, to characterise mutations and the utility of using off-target sequences to detect genomic imbalances in Multiple Myeloma patients.
… for downstream analyses. Germline/tumour batch effects were identified from insert-size, coverage, and enrichment data. Systematic literature reviewal elucidated 105-MM-associated genes recurrently targeted in MM patients, in which MM1-MM6 sequence variant annotation/filtering extracted …
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Enhanced evaluation of RNA expression in Esophageal Cancer tissues: Combining Microarray and RNA-Sequence approaches
… preprocessing, alignment, and quantification. Batch effects deriving from study-specific variation were handled using ComBat-seq prior to differential expression analysis with DESeq2. Gene set enrichment analysis was then performed using FGSEA against curated pathway databases to uncover …
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Development of An In Silico Kir Genotyping Algorithm and Its Application to Population and Cancer Immunogenetic Analyses
… The analysis also revealed significant batch effects due to disparities in the lengths of sequence reads produced by different sequencing centers. SeRRAMC processing is the first approach to enable these types of immunogenetic analyses. It also offers the first solution for quantifying …
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Computational analysis and method development for high throughput transcriptomics and transcriptional regulatory inference in plants
… these expression changes by distinguishing the effects from the transcription and alternative splicing. </p><p class="MsoNormal">We performed a high resolution ultra-deep RNA-seq time-course experiment to study Arabidopsis in response to cold treatment where plants were grown at 20<sup>o</sup>C …
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Computational methods for single cell RNA and genome assembly resolution using genetic variation
… complex data. In single cell RNAseq, problems of batch effects, doublets, and ambient RNA are each sources of noise that impede our ability to infer the functional states of cells and compare them between experiments. One new popular new experimental design promising to solve each of these while …
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Hierarchical Inference in Gaussian Processes
… adapting the kernel design to account for random effects, and technical and biological confounders like batch effects into the hierarchical construction. The low-dimensional latent space revealed biologically relevant clusters and in comparison to existing techniques (analysed on the same data …
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Discovering variation from cell atlases: comparative methods for single-cell genomics
… discovery rate control even in the presence of batch effects. I present a comprehensive benchmark against alternative differential abundance testing strategies, using simulations and scRNA-seq data. I then demonstrate the utility of Milo by studying perturbations across lineages in a dataset of …
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Systems biology of lung diseases: a multi-perspective view from host and pathogen
… systems biology that try to account for the effects of the multitude of molecular components and their interactions that comprise both the human host and microbial pathogens. The biomarker discovery field is replete with molecular signatures that have not translated into the clinic despite …
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