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RNA from each sample was also analyzed for actin RNA copies to use as a means for normalization.
Comparing results from multiple RNAseq runs requires means for normalization, accounting for batch effects and sample-to-sample variability.
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Differential expression was investigated using the edgeR (Robinson et al. 2010) package in R (R Core Team 2013), which implements a negative binomial distribution for the modeling of gene expression and uses the trimmed mean of M-values approach (Robinson and Oshlack 2010) for calculating a mean for normalization.
We propose it as a means for testing biological hypotheses and appropriateness of normalization.
Fold changes were first converted to log2 and expressed relative to the mean value for normalization.
All arrays were scaled to the same mean value for normalization (200) and were summarized by a log2 scale average using 1-step Tukey biweight.
However, 18S rRNA expression is monitored primarily to double check for substantial anomalies in mRNA quantification when positive results are found, rather than as a precise means of normalization for results which appear consistent.
Absolute concentration values are usually obtained by means of normalization procedures that correct for differing propensities of proteins to produce identifiable fragmentation spectra.
The relative quantities of the reference genes Hprt, Ywhaz, B2 m, and Actb were determined, and a normalization factor was calculated based on the geometric mean for internal normalization.
Mean normalization was conducted for each phenotype by first dividing the average of each GSL genotype within an environment to the corresponding population mean for each environment.
The endogenous controls RPL13A, HPRT1 and GUSB were combined using the dataAssist software V1.0 and "arithmetic mean" as method for normalization.
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