Hello, I am dealing with solexa pared-end RNA-seq data of bacteria. Now I use cufflinks tools to caculate FPKM, then I can analyze differential expression genes, but when I compare FPKM value and single-resolution coverage of a gene, I find FPKM of some genes are very high, such as, FPKM value is 4800, but each base of these genes' coverage(or number of reads) is low, such as read number of each base among a gene is about 10, so could someone help me: why the coverage of each base among a gene is so low when FPKM is very high? How to explain this? Does it need to do FPKM normalization? Thank you!
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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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