Statistical Analysis

PROPER – Comprehensive Power Evaluation for Differential Expression using RNA-seq

rna-seq

RNA-seq has become a routine technique in differential expression (DE) identification. Scientists face a number of experimental design decisions including the sample size. The power for detecting differential expression is affected by several factors including the fraction of DE genes, ...

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Power analysis and sample size estimation for RNA-Seq differential expression

rna-seq

It is crucial for researchers to optimize RNA-seq experimental designs for differential expression detection. Currently, the field lacks general methods to estimate power and sample size for RNA-Seq in complex experimental designs, under the assumption of the negative binomial distribution. ...

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subSeq – Determining appropriate sequencing depth through efficient read subsampling

rna-seq

Next-generation sequencing experiments, such as RNA-Seq, play an increasingly important role in biological research. One complication is that the power and accuracy of such experiments depends substantially on the number of reads sequenced, so it is important and challenging to ...

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Study finds RNA-Seq, like microarrays, only accurate for relative expression, not absolute quantitation

rna-seq

The collborators at the SEQC/MAQC-III Consortium present primary results from the Sequencing Quality Control (SEQC) project, coordinated by the US Food and Drug Administration. Examining Illumina HiSeq, Life Technologies SOLiD and Roche 454 platforms at multiple laboratory sites using reference ...

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The concordance between RNA-seq and microarray data depends on chemical treatment and transcript abundance

rna-seq

The concordance of RNA-sequencing (RNA-seq) with microarrays for genome-wide analysis of differential gene expression has not been rigorously assessed using a range of chemical treatment conditions. Here a team led by researchers atuse at the US FDA comprehensive study design ...

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The correlation coefficient alone is not sufficient to assess equality among sample replicates

Reliability and reproducibility are key metrics for gene expression assays. This report assesses the utility of the correlation coefficient in the analysis of reproducibility and reliability of gene expression data. The correlation coefficient alone is not sufficient to assess equality ...

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An integrative method to normalize RNA-Seq data

rna-seq

Transcriptome sequencing is a powerful tool for measuring gene expression, but as well as some other technologies, various artifacts and biases affect the quantification. In order to correct some of them, several normalization approaches have emerged, differing both in the ...

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