I am interested in comparing the distribution of my samples (individually) with that of the model of my entire dataset (comparing using KS test with simulated/boostraped data). I am hoping to rationalise exclusion of several samples by this method. Where can I find the estimated mean, variance for the model fitted to my data within the program? I hope someone can point me in the right direction. Also apologies if my description is inaccurate/unintelligible.
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The field of epigenetics has traditionally concentrated more on DNA and how changes like methylation and phosphorylation of histones impact gene expression and regulation. However, our increased understanding of RNA modifications and their importance in cellular processes has led to a rise in epitranscriptomics research. “Epitranscriptomics brings together the concepts of epigenetics and gene expression,” explained Adrien Leger, PhD, Principal Research Scientist...-
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Proteins are often described as the workhorses of the cell, and identifying their sequences is key to understanding their role in biological processes and disease. Currently, the most common technique used to determine protein sequences is mass spectrometry. While still a valuable tool, mass spectrometry faces several limitations and requires a highly experienced scientist familiar with the equipment to operate it. Additionally, other proteomic methods, like affinity assays, are constrained...-
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