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That's very interesting, ignoring UTR mapped reads to remove the bias in rna-seq data! -
Thanks!
thanks Pascal, this study is just what I was looking for. very comprehensive too. many thanks .
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You might wanna take a look at this publication:
Ramsköld,D. et al. (2009) An abundance of ubiquitously expressed genes revealed by tissue transcriptome sequence data. PLoS computational biology, 5, e1000598.Leave a comment:
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house-keeping genes in RNA-seq data sets?
Hi All,
Does anyone out there know of a good reference or two on the depth of coverage required to cover most transcripts and gauge expression levels in RNA-seq experiments? In particular, can anyone give me an idea of what percentage of sequences in their RNA-seq data sets are from what you would consider house-keeping genes? I have one reference in yeast from Wilhelm and Landry (2009) but I can't seem to find much else.
many thanks . . .
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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...04-22-2024, 07:01 AM -
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...04-04-2024, 04:25 PM
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