RNA Seq Analysis Papers

• A reanalysis of mouse ENCODE comparative gene expression data [version 1; peer review: 3 approved, 1 approved with reservations]
• RNA-seq analysis is easy as 1-2-3 with limma, Glimma and edgeR [version 1; peer review: 3 approved]
• Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding
• Selecting Between-Sample RNA-Seq Normalization Methods from the Perspective of their Assumptions
• S-IRFindeR: stable and accurate measurement of intron retention
• Curation of over 10,000 transcriptomic studies to enable data reuse
• Salmon: Accurate, Versatile and Ultrafast Quantification from RNA-seq Data using Lightweight-Alignment
• On the widespread and critical impact of systematic bias and batch effects in single-cell RNA-Seq data
• A Comparison of Methods: Normalizing High-Throughput RNA Sequencing Data
• The impact of amplification on di↵erential expression analyses by RNA-seq
• Fast and accurate single-cell RNA-Seq analysis by clustering of transcript-compatibility counts
• Dumpster diving in RNA-sequencing to find the source of every last read
• Differential analysis of RNA-Seq incorporating quantification uncertainty
• Batch effects and the effective design of single-cell gene expression studies
• Assessment of single cell RNA-seq normalization methods
• CIDR: Ultrafast and accurate clustering through imputation for single cell RNA-Seq data
• Power Analysis of Single Cell RNA‐Sequencing Experiments
• Overcoming confounding plate effects in differential expression analyses of single-cell RNA-seq data
• A framework for RNA quality correction in differential expression analysis
• MetaSRA: normalized sample-specic metadata for the Sequence Read Archive
• Bias, robustness and scalability in differential expression analysis of single-cell RNA-seq data
• SQUID: Transcriptomic Structural Variation Detection from RNA-seq
• Thousands of large-scale RNA sequencing experiments yield a comprehensive new human gene list and reveal extensive transcriptional noise
• A step-by-step workflow for low-level analysis of single-cell RNA-seq data [version 1; peer review: 5 approved with reservations]
• Genome-wide repressive capacity of promoter DNA methylation is revealed through epigenomic manipulation
• Extracting allelic read counts from 250,000 human sequencing runs in Sequence Read Archive
• RNA Sequencing Data: Hitchhiker's Guide to Expression Analysis
• A comprehensive evaluation of normalization methods for Illumina high-throughput RNA sequencing data analysis
• Gene set analysis approaches for RNA-seq data: performance evaluation and application guideline
• Comparative evaluation of isoform-level gene expression estimation algorithms for RNA-seq and exon-array platforms
• Comparison of methods to detect differentially expressed genes between single-cell populations
• Benchmark analysis of algorithms for determining and quantifying full-length mRNA splice forms from RNA-seq data
• Swimming downstream: statistical analysis of differential transcript usage following Salmon quantification [version 1; peer review: 3 approved with reservations]
• Differential analyses for RNA-seq: transcript-level estimates improve gene-level inferences [version 2; peer review: 2 approved]
• Count-based differential expression analysis of RNA sequencing data using R and Bioconductor
• Pathway enrichment analysis and visualization of omics data using g:Profiler, GSEA, Cytoscape and EnrichmentMap
• Normalizing single-cell RNA sequencing data: Challenges and opportunities
• From reads to genes to pathways: differential expression analysis of RNA-Seq experiments using Rsubread and the edgeR quasi-likelihood pipeline [version 2; peer review: 5 approved]
• Single-Cell Transcriptomics Bioinformatics and Computational Challenges
• iRNA-seq: computational method for genome-wide assessment of acute transcriptional regulation from total RNA-seq data
• Comprehensive evaluation of fusion transcript detection algorithms and a meta-caller to combine top performing methods in paired-end RNA-seq data
• Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression
• Normalization of RNA-seq data using factor analysis of control genes or samples
• HISAT: a fast spliced aligner with low memory requirements
• StringTie enables improved reconstruction of a transcriptome from RNA-seq reads
• Ballgown bridges the gap between transcriptome assembly and expression analysis
• Transcript-level expression analysis of RNA-seq experiments with HISAT, StringTie, and Ballgown
• The contribution of cell cycle to heterogeneity in single-cell RNA-seq data
• Differential gene and transcript expression analysis of RNA-Seq experiments with TopHat and Cufflinks
• Translating RNA sequencing into clinical diagnostics: opportunities and challenges
• Tackling the widespread and critical impact of batch effects in high-throughput data
• Geometry of the Gene Expression Space of Individual Cells
• Cross-platform normalization of microarray and RNA-seq data for machine learning applications
• Union Exon Based Approach for RNA-Seq Gene Quantification: To Be or Not to Be?
• Reproducibility of high-throughput mRNA and small RNA sequencing across laboratories
• RNA sequencing: the teenage years
• Errors in RNA-Seq quantification affect genes of relevance to human disease
• Comparing the normalization methods for the differential analysis of Illumina highthroughput RNA-Seq data
• A comprehensive evaluation of ensembl, RefSeq, and UCSC annotations in the context of RNA-seq read mapping and gene quantification
• QuickRNASeq lifts large-scale RNA-seq data analyses to the next level of automation and interactive visualization
• Tools and best practices for data processing in allelic expression analysis
• Meta-analysis of RNA-seq expression data across species, tissues and studies
• Isoform prefiltering improves performance of count-based methods for analysis of differential transcript usage
• A survey of best practices for RNA-seq data analysis
• Design and computational analysis of single-cell RNA-sequencing experiments
• A benchmark for RNA-seq quantification pipelines
• Comprehensive analyses of tumor immunity: implications for cancer immunotherapy
• Accuracy assessment of fusion transcript detection via read-mapping and de novo fusion transcript assembly-based methods
• A practical guide to single-cell RNAsequencing for biomedical research and clinical applications
• Comparative assessment of methods for the fusion transcripts detection from RNA-Seq data
• voom: precision weights unlock linear model analysis tools for RNA-seq read counts