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Integrating gene expression profiles across different platforms

Integrating gene expression profiles across different platforms

Determining differentially expressed genes (DEGs) between biological samples is the key to understand how genotype gives rise to phenotype. RNA-seq and microarray are two main technologies for profiling gene expression levels. However, considerable discrepancy has been found between DEGs detected ...

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RNA-Seq analysis in SeqMonk with DESeq

RNA-Seq analysis in SeqMonk with DESeq

This video shows a walk-through of a full 2-condition, 3-replicate RNA-Seq experiment, from loading the data, through QC, quantitation and differential expression analysis using both DESeq2 and SeqMonk’s own Intensity Difference filter. http://www.bioinformatics.babraham.ac.uk/projects/seqmonk/

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Optimization of miRNA-seq data preprocessing

Optimization of miRNA-seq data preprocessing

The past two decades of microRNA (miRNA) research has solidified the role of these small non-coding RNAs as key regulators of many biological processes and promising biomarkers for disease. The concurrent development in high-throughput profiling technology has further advanced our ...

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

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

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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