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I hadn't actually seen it before, but it is a very good looking web app! The power estimates should be similar, but won't be identical for 2 reasons:
1. Scotty assumes that variance follows a lognormal distribution. I think this is a valid and logical assumption. RNASeqPower uses the measured variance from the data instead.
2. Scotty pseudo-randomly selects 200 values from a 2 dimensional matrix (variance and depth) then uses that mean as the power of the dataset. The way we use RNASeqPower is to say that we want to know the minimum requirements to reach the desired power. We need to know two things, how many genes do I want to detect and how much variance to I want to allow. If you only want to detect the top 90% of genes, then you take the 10th percentile of gene counts for your pilot (all other genes will have more than this count). You do the same for variance except you select the 90th percentile of variance. Using the minimum read count and the maximum allowable variance, that is the power you have in your experiment. Granted most genes will have higher power since they will have lower variance and higher counts. So in the end, it comes down to how you define what power actually means.
RNASeqPower can also give you the power for each gene in a dataset.
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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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