voom: precision weights unlock linear model analysis tools for RNA-seq read counts
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47,038 citations
Cites methods from "voom: precision weights unlock line..."
...Other methods compared were the voom normalization method followed by linear modeling using the limma package [35] and the SAMseq permutation method of the samr package [23]....
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22,147 citations
Cites background or methods or result from "voom: precision weights unlock line..."
...One way is through estimating a mean-variance trend, which can either be incorporated into the empirical Bayes procedure as mentioned above or used to generate observation weights (10)....
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...Both observationlevel (2,10,43) and sample-specific weights (11) can be used in an analysis....
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...The resulting pipeline gives comparable performance to the best of the negative binomial-based software packages but with greater speed and reliability for large data sets (10,21)....
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...First, the global variance estimate can now incorporate a mean-variance trend (10,17,18)....
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17,014 citations
Cites methods from "voom: precision weights unlock line..."
...Other methods compared were the voom normalization method followed by linear modeling using the limma package [35] and the SAMseq permutation method of the samr package [23]....
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14,103 citations
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References
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"voom: precision weights unlock line..." refers background or methods in this paper
...Specifically we used the goodTuringProportions function of the edgeR package [12], which implements the Good-Turing algorithm [55], to predict the true proportion of total RNA attributable to each gene....
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...One common approach to summarize RNA-seq data is to count the number of sequence reads mapping to each gene or genomic feature of interest [11, 12, 13, 14]....
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23,215 citations
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"voom: precision weights unlock line..." refers background or methods or result in this paper
...The performance of voom and limma-trend is compared to that of edgeR, DESeq, baySeq, TSPM, PoissonSeq, and DSS. Simulation studies show that the limma-based pipelines more than hold their own against the count-based RNA-seq meth- ods in terms of power and error rate control even when the data are generated according to the assumptions of the earlier methods....
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...The voom mean-variance trend is shown in Figure 1b. Software The results presented in this article are carried out using R version 3.0.0 and software packages limma 3.16.2, edgeR 3.2.3, baySeq 1.14.1, DESeq 1.12.0, DSS 1.4.0, PoissonSeq 1.1.2 and tweeDEseqCountData 1.0.8....
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...For example, it would be at least as scientifically reasonable to assume that the true expression levels for each gene follow a log-normal distribution between replicates instead of a gamma distribution, and such an assumption would tend to improve the performance of voom relative to edgeR, DESeq, baySeq and DSS....
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...When the library sizes are unequal, DSS and DESeq became extremely conservative....
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...TMM-scale normalization [54] was used for all the analysis methods, except for DESeq and PoissonSeq, which have their own built-in normalization methods....
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