Expression and Quantification

Methods for Joint Imaging and RNA-seq Data Analysis

rna-seq

Emerging integrative analysis of genomic and anatomical imaging data which has not been well developed, provides invaluable information for the holistic discovery of the genomic structure of disease and has the potential to open a new avenue for discovering novel ...

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Comparison of Computational Methods for Identification of Allele-Specific Expression based on Next Generation Sequencing Data

rna-seq

Allele-specific expression (ASE) studies have wide-ranging implications for genome biology and medicine. Whole transcriptome RNA sequencing (RNA-Seq) has emerged as a genome-wide tool for identifying ASE, but suffers from mapping bias favoring reference alleles. Two categories of methods are adopted ...

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MIRPIPE – quantification of microRNAs in niche model organisms

rna-seq

MicroRNAs represent an important class of small non-coding RNAs regulating gene expression in eukaryotes. Present algorithms typically rely on genomic data to identify miRNAs and require extensive installation procedures. Niche model organisms lacking genomic sequences cannot be analyzed by such ...

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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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Correction of gene expression data: performance-dependency on inter-replicate and inter-treatment biases

rn-seq

This report investigates for the first time the potential inter-treatment bias source of cell number for gene expression studies. Cell-number bias can affect gene expression analysis when comparing samples with unequal total cellular RNA content or with different RNA extraction ...

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A Comparative Study of Techniques for Differential Expression Analysis on RNA-Seq Data

rna-seq

Recent advances in next-generation sequencing technology allow high-throughput cDNA sequencing (RNA-Seq) to be widely applied in transcriptomic studies, in particular for detecting differentially expressed genes between groups. Many software packages have been developed for the identification of differentially expressed genes ...

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shRNA-seq data analysis with edgeR

rna-seq

Pooled short hairpin RNA sequencing (shRNA-seq) screens are becoming increasingly popular in functional genomics research, and there is a need to establish optimal analysis tools to handle such data. This open-source shRNA processing pipeline in edgeR provides a complete analysis ...

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Long Intergenic Non-Coding RNAs (LincRNAs) Identified by RNA-Seq

rna-seq

In an attempt to find breast cancer tissue and respective adjacent normal tissue were studied for the expression of lincRNAs by RNA-seq. Among the 538 lincRNAs studied, 124 lincRNAs were exclusively expressed in cancer adjacent tissues and 62 lincRNAs were ...

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Corset – differential gene expression analysis for de novo assembled transcriptomes

rna-seq

Next generation sequencing has made it possible to perform differential gene expression studies in non-model organisms. For these studies, the need for a reference genome is circumvented by performing de novo assembly on the RNA-seq data. However, transcriptome assembly produces ...

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bagSVM – Classification of RNA-Seq Data via Bagging Support Vector Machines

RNA sequencing (RNA-Seq) is a powerful technique for transcriptome profiling of the organisms that uses the capabilities of next-generation sequencing (NGS) technologies. Recent advances in NGS let to measure the expression levels of tens to thousands of transcripts simultaneously. Using ...

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