Thank you very much for your website and all of your help. I am attempting to use IGV to look at a few genes in order to calculate the number of non-synonymous SNPs. However, there were large regions where the number of reads dropped from 10000 to as low as 500. If we find that there is a region with a high rate of nonsynonymous SNPs but it only contains an average of 500 reads at that point is that significant if other regions contain 5000 reads? In other words, if a single nucleotide shows 5% variability (eg 95% A and 5%T) with 500 reads is that similar to 5% variability at 5000 reads? Or do we need to treat the 4500 reads not showing up in IGV at that spot as potentially too dissimilar to run statistical analysis? Any help or references you could provide would be much appreciated.
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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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