[HTML][HTML] tappAS: a comprehensive computational framework for the analysis of the functional impact of differential splicing
L de la Fuente, Á Arzalluz-Luque, M Tardáguila… - Genome biology, 2020 - Springer
Recent advances in long-read sequencing solve inaccuracies in alternative transcript
identification of full-length transcripts in short-read RNA-Seq data, which encourages the …
identification of full-length transcripts in short-read RNA-Seq data, which encourages the …
Identifying differentially spliced genes from two groups of RNA-seq samples
Recent study revealed that most human genes have alternative splicing and can produce
multiple isoforms of transcripts. Differences in the relative abundance of the isoforms of a …
multiple isoforms of transcripts. Differences in the relative abundance of the isoforms of a …
Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation
High-throughput mRNA sequencing (RNA-Seq) promises simultaneous transcript discovery
and abundance estimation,,. However, this would require algorithms that are not restricted …
and abundance estimation,,. However, this would require algorithms that are not restricted …
Accurate detection of differential RNA processing
Deep transcriptome sequencing (RNA-Seq) has become a vital tool for studying the state of
cells in the context of varying environments, genotypes and other factors. RNA-Seq profiling …
cells in the context of varying environments, genotypes and other factors. RNA-Seq profiling …
Transcriptome assembly and isoform expression level estimation from biased RNA-Seq reads
Motivation: RNA-Seq uses the high-throughput sequencing technology to identify and
quantify transcriptome at an unprecedented high resolution and low cost. However, RNA …
quantify transcriptome at an unprecedented high resolution and low cost. However, RNA …
bayNorm: Bayesian gene expression recovery, imputation and normalization for single-cell RNA-sequencing data
Motivation Normalization of single-cell RNA-sequencing (scRNA-seq) data is a prerequisite
to their interpretation. The marked technical variability, high amounts of missing …
to their interpretation. The marked technical variability, high amounts of missing …
Methods to study splicing from high-throughput RNA sequencing data
The development of novel high-throughput sequencing (HTS) methods for RNA (RNA-Seq)
has provided a very powerful mean to study splicing under multiple conditions at …
has provided a very powerful mean to study splicing under multiple conditions at …
STARsolo: accurate, fast and versatile mapping/quantification of single-cell and single-nucleus RNA-seq data
We present STARsolo, a comprehensive turnkey solution for quantifying gene expression in
single-cell/nucleus RNA-seq data, built into RNA-seq aligner STAR. Using simulated data …
single-cell/nucleus RNA-seq data, built into RNA-seq aligner STAR. Using simulated data …
Deep-learning augmented RNA-seq analysis of transcript splicing
A major limitation of RNA sequencing (RNA-seq) analysis of alternative splicing is its
reliance on high sequencing coverage. We report DARTS (https://github …
reliance on high sequencing coverage. We report DARTS (https://github …
Bubble: a fast single-cell RNA-seq imputation using an autoencoder constrained by bulk RNA-seq data
Single-cell RNA-sequencing technology (scRNA-seq) brings research to single-cell
resolution. However, a major drawback of scRNA-seq is large sparsity, ie expressed genes …
resolution. However, a major drawback of scRNA-seq is large sparsity, ie expressed genes …