Statistical Analysis

The impact of quality filter for RNA-Seq

rna-seq

With the emergence of large-scale sequencing platforms since 2005, there has been a great revolution regarding methods for decoding DNA sequences, which have also affected quantitative and qualitative gene expression analyses through the RNA-Sequencing technique. However, issues related to the ...

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Reduction of Gene Expression Variability from Single Cells to Populations follows Simple Statistical Laws

rna-seq

Recent studies on single cells and population transcriptomics have revealed striking differences in global gene expression distributions. Single cells display highly variable expressions between cells, while cell populations present deterministic global patterns. The mechanisms governing the reduction of transcriptome-wide variability ...

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The statistical universe is a single patient – pathway analysis from “N-of-1” RNA-Seq data

rna-seq

The emergence of precision medicine allowed the incorporation of individual molecular data into patient care. Indeed, DNA sequencing predicts somatic mutations in individual patients. However, these genetic features overlook dynamic epigenetic and phenotypic response to therapy. Meanwhile, accurate personal transcriptome ...

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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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Quality control method for RNA-seq using single nucleotide polymorphism allele frequency

rna-seq

RNA sequencing (RNA-seq) provides information not only about the level of expression of individual genes but also about genomic sequences of host cells. When we use transcriptome data with whole-genome single nucleotide polymorphism (SNP) variant information, the allele frequency can ...

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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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