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Obstacles to detecting isoforms using full-length scRNA-seq data.
BACKGROUND:Early single-cell RNA-seq (scRNA-seq) studies suggested that it was unusual to see more than one isoform being produced from a gene in a single cell, even when multiple isoforms were detected in matched bulk RNA-seq...
Published by: Genome biology
Obstacles to detecting isoforms using full-length scRNA-seq data
Abstract: Background: Early single-cell RNA-seq (scRNA-seq) studies suggested that it was unusual to see more than one isoform being produced from a gene in a single cell, even when multiple isoforms were detected in matched...
Practical guidelines for the comprehensive analysis of ChIP-seq data.
Timothy Bailey, Pawel Krajewski, Istvan Ladunga, Celine Lefebvre, Qunhua Li, Tao Liu, Pedro Madrigal, Cenny Taslim, Jie Zhang
Jun 19, 2020
Mapping the chromosomal locations of transcription factors, nucleosomes, histone modifications, chromatin remodeling enzymes, chaperones, and polymerases is one of the key tasks of modern biology, as evidenced by the...
Obstacles to detecting isoforms using full-length scRNA-seq data
Abstract: Background: Early single-cell RNA-seq (scRNA-seq) studies suggested that it was unusual to see more than one isoform being produced from a gene in a single cell, even when multiple isoforms were detected in matched...
Computational approaches for interpreting scRNA-seq data.
The recent developments in high-throughput single-cell RNA sequencing technology (scRNA-seq) have enabled the generation of vast amounts of transcriptomic data at cellular resolution. With these advances come new modes of data...
Simulation-based benchmarking of isoform quantification in single-cell RNA-seq.
Single-cell RNA-seq has the potential to facilitate isoform quantification as the confounding factor of a mixed population of cells is eliminated. However, best practice for using existing quantification methods has not been...
scNMT-seq enables joint profiling of chromatin accessibility DNA methylation and transcription in single cells.
Stephen J Clark, Ricard Argelaguet, Chantriolnt-Andreas Kapourani, Thomas M Stubbs, Heather J Lee, Celia Alda-Catalinas, Felix Krueger, Guido Sanguinetti, Gavin Kelsey, John C Marioni, Oliver Stegle, Wolf Reik
Sep 26, 2018
Parallel single-cell sequencing protocols represent powerful methods for investigating regulatory relationships, including epigenome-transcriptome interactions. Here, we report a single-cell method for parallel chromatin...
Genome-wide analysis of DNA replication and DNA double-strand breaks using TrAEL-seq.
Faithful replication of the entire genome requires replication forks to copy large contiguous tracts of DNA, and sites of persistent replication fork stalling present a major threat to genome stability. Understanding the...
f-scLVM
Florian Buettner, Naruemon Pratanwanich, Davis J McCarthy, John C Marioni, Oliver Stegle
Mar 26, 2018
Single-cell RNA-sequencing (scRNA-seq) allows studying heterogeneity in gene expression in large cell populations. Such heterogeneity can arise due to technical or biological factors, making decomposing sources of variation...
Gene set annotations Single-cell RNA-seq Sparse factor analysis Animals Computer Simulation Databases as Topic Factor Analysis Statistical Gene Expression Regulation Mice Models Theoretical Mouse embryonic stem cells Neurons Reproducibility of Results Sequence Analysis RNA Single-Cell Analysis Software
Classification of low quality cells from single-cell RNA-seq data.
Tomislav Ilicic, Jong Kyoung Kim, Aleksandra A Kolodziejczyk, Frederik Otzen Bagger, Davis James McCarthy, John C Marioni, Sarah A Teichmann
May 16, 2019
Single-cell RNA sequencing (scRNA-seq) has broad applications across biomedical research. One of the key challenges is to ensure that only single, live cells are included in downstream analysis, as the inclusion of compromised...
Mapping eQTLs with RNA-seq reveals novel susceptibility genes, non-coding RNAs and alternative-splicing events in systemic lupus erythematosus.
Christopher A Odhams, Andrea Cortini, Lingyan Chen, Amy L Roberts, Ana Viñuela, Alfonso Buil, Kerrin S Small, Emmanouil T Dermitzakis, David L Morris, Timothy J Vyse, Deborah S Cunninghame Graham
Nov 26, 2019
Studies attempting to functionally interpret complex-disease susceptibility loci by GWAS and eQTL integration have predominantly employed microarrays to quantify gene-expression. RNA-Seq has the potential to discover a more...
Alternative Splicing Carbon-Nitrogen Ligases with Glutamine as Amide-N-Donor Chromosome Mapping Female Gene Expression Regulation Genetic Predisposition to Disease Genome-Wide Association Study Haplotypes Humans Lupus Erythematosus Systemic Male Polymorphism Single Nucleotide Quantitative Trait Loci RNA Untranslated T Cell Transcription Factor 1
A Neural Network Approach for the Analysis of Reproducible Ribo–Seq Profiles
In recent years, the Ribosome profiling technique (Ribo–seq) has emerged as a powerful method for globally monitoring the translation process in vivo at single nucleotide resolution. Based on deep sequencing of mRNA...
Giorgia Giacomini, Caterina Graziani, Veronica Lachi, Pietro Bongini, Niccolò Pancino, Monica Bianchini, Davide Chiarugi, Angelo Valleriani, Paolo Andreini
Aug 05, 2022
Refining the transcriptome of the human malaria parasite Plasmodium falciparum using amplification-free RNA-seq
Lia Chappell, Philipp Ross, Lindsey Orchard, Timothy J. Russell, Thomas D. Otto, Matthew Berriman, Julian C. Rayner, Manuel Llinás
Jun 08, 2021
Abstract: Background: Plasmodium parasites undergo several major developmental transitions during their complex lifecycle, which are enabled by precisely ordered gene expression programs. Transcriptomes from the 48-h blood...
Discrete distributional differential expression (D3E)--a tool for gene expression analysis of single-cell RNA-seq data.
BACKGROUND: The advent of high throughput RNA-seq at the single-cell level has opened up new opportunities to elucidate the heterogeneity of gene expression. One of the most widespread applications of RNA-seq is to identify...
Characterizing noise structure in single-cell RNA-seq distinguishes genuine from technical stochastic allelic expression.
Jong Kyoung Kim, Aleksandra A Kolodziejczyk, Tomislav Ilicic, Sarah A Teichmann, John C Marioni
May 16, 2019
Single-cell RNA-sequencing (scRNA-seq) facilitates identification of new cell types and gene regulatory networks as well as dissection of the kinetics of gene expression and patterns of allele-specific expression. However, to...
Visualization and analysis of RNA-Seq assembly graphs.
Fahmi W Nazarie, Barbara Shih, Tim Angus, Mark W Barnett, Sz-Hau Chen, Kim M Summers, Karsten Klein, Geoffrey J Faulkner, Harpreet K Saini, Mick Watson, Stijn van Dongen, Anton J Enright, Tom C Freeman
Jan 21, 2020
RNA-Seq is a powerful transcriptome profiling technology enabling transcript discovery and quantification. Whilst most commonly used for gene-level quantification, the data can be used for the analysis of transcript isoforms....
Automated methods for cell type annotation on scRNA-seq data.
The advent of single-cell sequencing started a new era of transcriptomic and genomic research, advancing our knowledge of the cellular heterogeneity and dynamics. Cell type annotation is a crucial step in analyzing single-cell...
Refining the transcriptome of the human malaria parasite Plasmodium falciparum using amplification-free RNA-seq.
Lia Chappell, Philipp Ross, Lindsey Orchard, Timothy J Russell, Thomas D Otto, Matthew Berriman, Julian C Rayner, Manuel Llinás
Aug 07, 2020
BACKGROUND: Plasmodium parasites undergo several major developmental transitions during their complex lifecycle, which are enabled by precisely ordered gene expression programs. Transcriptomes from the 48-h blood stages of the...
High-throughput total RNA sequencing in single cells using VASA-seq.
Fredrik Salmen, Joachim De Jonghe, Tomasz S Kaminski, Anna Alemany, Guillermo E Parada, Joe Verity-Legg, Ayaka Yanagida, Timo N Kohler, Nicholas Battich, Floris van den Brekel, Anna L Ellermann, Alfonso Martinez Arias, Jennifer Nichols, Martin Hemberg, Florian Hollfelder, Alexander van Oudenaarden
Dec 15, 2022
Most methods for single-cell transcriptome sequencing amplify the termini of polyadenylated transcripts, capturing only a small fraction of the total cellular transcriptome. This precludes the detection of many long non-coding...
Refining the transcriptome of the human malaria parasite Plasmodium falciparum using amplification-free RNA-seq
Lia Chappell, Philipp Ross, Lindsey Orchard, Timothy J. Russell, Thomas D. Otto, Matthew Berriman, Julian C. Rayner, Manuel Llinás
Jun 08, 2020
Abstract: Background: Plasmodium parasites undergo several major developmental transitions during their complex lifecycle, which are enabled by precisely ordered gene expression programs. Transcriptomes from the 48-h blood...
scRNA-Seq reveals distinct stem cell populations that drive hair cell regeneration after loss of Fgf and Notch signaling.
Mark E Lush, Daniel C Diaz, Nina Koenecke, Sungmin Baek, Helena Boldt, Madeleine K St Peter, Tatiana Gaitan-Escudero, Andres Romero-Carvajal, Elisabeth M Busch-Nentwich, Anoja G Perera, Kathryn E Hall, Allison Peak, Jeffrey S Haug, Tatjana Piotrowski
Apr 29, 2019
Loss of sensory hair cells leads to deafness and balance deficiencies. In contrast to mammalian hair cells, zebrafish ear and lateral line hair cells regenerate from poorly characterized support cells. Equally ill-defined is the...
A step-by-step workflow for low-level analysis of single-cell RNA-seq data with Bioconductor.
Single-cell RNA sequencing (scRNA-seq) is widely used to profile the transcriptome of individual cells. This provides biological resolution that cannot be matched by bulk RNA sequencing, at the cost of increased technical noise...
Parallel factor ChIP provides essential internal control for quantitative differential ChIP-seq.
A key challenge in quantitative ChIP combined with high-throughput sequencing (ChIP-seq) is the normalization of data in the presence of genome-wide changes in occupancy. Analysis-based normalization methods were developed for...
Laplacian Likelihood-Based Generalized Additive Model for RNA-Seq Analysis of Oral Squamous Cell Carcinoma
The study's objective is to identify the non-linear relationship of differentially expressed genes that vary in terms of the tumour and normal tissue and correct for any variations among the RNA-Seq experiment focused on Oral...
Published by: IGI Global Scientific Publishing
Single cell RNA-seq and ATAC-seq analysis of cardiac progenitor cell transition states and lineage settlement.
Guangshuai Jia, Jens Preussner, Xi Chen, Stefan Guenther, Xuejun Yuan, Michail Yekelchyk, Carsten Kuenne, Mario Looso, Yonggang Zhou, Sarah Teichmann, Thomas Braun
May 14, 2019
Formation and segregation of cell lineages forming the heart have been studied extensively but the underlying gene regulatory networks and epigenetic changes driving cell fate transitions during early cardiogenesis are still...
Animals Body Patterning Cell Differentiation Cell Lineage Chromatin Embryo Mammalian Gene Expression Regulation Developmental Gene Regulatory Networks Homeobox Protein Nkx-2.5 LIM-Homeodomain Proteins Mice Mice Inbred C57BL Mice Transgenic Mouse embryonic stem cells Myocytes Cardiac Sequence Analysis RNA Signal Transduction Single-Cell Analysis Transcription Factors Transcriptome
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