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High-throughput single-cell RNA-seq (scRNA-seq) is a powerful tool for studying gene ... expression in single cells. Most current scRNA-seq bioinformatics tools focus on analysing overall expression ... data gene...
scRNA-seq datasets are increasingly used to identify gene...
Many computational methods have been developed recently to analyze single-cell RNA-seq (scRNA-seq) data. Several benchmark studies have compared ... Yet, given the biological diversity of scRNA-seq datasets, para...
High-throughput sequencing of RNAs crosslinked to Argonaute proteins reveals not only a multitude of atypical miRNA binding sites but also of miRNA targets with atypical functions, and can be used to infer qua...
Single-cell RNA sequencing has been widely adopted to estimate the cellular composition of heterogeneous tissues and obtain transcriptional profiles of individual cells. Multiple approaches for optimal sample ...
We report the first genome-wide ChIP-seq map for CIITA and complement this by...trans with a CIITA intronic sequence variant, integrate with CIITA recruitment and show how this is mediated by allele-specific recr...
The advent of single-cell RNA-sequencing (scRNA-seq) has driven significant computational methods development for all steps in the scRNA-seq data analysis pipeline, including filtering, normalization, ... combina...
Single-cell DNA methylation profiling currently suffers from excessive noise and/or limited cellular throughput. We developed scTAM-seq, a targeted bisulfite-free method for profiling ... low as 7%. We demonstrat...
We developed a multi-targeting RNA-immunoprecipitation sequencing (RIP-seq) strategy to reliably identify Sm-associated RNAs...Drosophila ovaries and cultured human cells. Using this method, we discovered three m...
The interaction between a pathogen and a host is a highly dynamic process in which both agents activate complex programs. Here, we introduce a single-cell RNA-sequencing method, scDual-Seq, that simultaneously ca...
Single-cell transcriptomics requires a method that is sensitive, accurate, and reproducible. Here, we present CEL-Seq2, a modified version of our CEL-Seq method, with threefold higher sensitivity, lower ... fibro...
We report a microfluidic system that physically separates nuclear RNA (nucRNA) and cytoplasmic RNA (cytRNA) from a single cell and enables single-cell integrated nucRNA and cytRNA-sequencing (SINC-seq). SINC-seq ...
Transcriptome assays are increasingly being performed by high-throughput RNA sequencing (RNA-seq). For organisms whose genomes have not...de novo from the RNA-seq data. Here, we present novel algorithms, ... and ...
Single-cell RNA-seq has the potential to facilitate isoform quantification ... The reduction in performance compared with bulk RNA-seq is small. An important biological insight comes ... genes that express two is...
We present SMURF-seq, a protocol to efficiently sequence short DNA ... them to form long molecules. Applying SMURF-seq using the Oxford Nanopore MinION yields up ... for read-counting applications. We apply SMURF...
The Author Correction to this article has been published in Genome Biology 2020 21:214
Open chromatin regions are correlated with active regulatory elements in development and are dysregulated in diseases. The BAF (SWI/SNF) complex is essential for development, and has been demonstrated to remod...
Despite its widespread use, RNA-seq is still too laborious and expensive to ... method. We present a novel approach, BRB-seq, which uses early multiplexing to produce 3 ... 2 hours of hands-on time. BRB-seq has a...
Dropout events in single-cell RNA sequencing (scRNA-seq) cause many transcripts to go undetected and ... This has triggered the development of bespoke scRNA-seq DE methods to cope with zero inflation. ... evaluat...
m6A is a ubiquitous RNA modification in eukaryotes. Transcriptome-wide m6A patterns in Arabidopsis have been assayed recently. However, differential m6A patterns between organs have not been well characterized.
We develop PIRCh-seq, a method which enables a comprehensive survey...
RNA-sequencing (RNA-seq) has a wide variety of applications, ... review all of the major steps in RNA-seq data analysis, including experimental design, quality ... of small RNAs and the integration of RNA-seq wit...
The Erratum to this article has been published in Genome Biology 2016 17:181
We introduce the use of Smed-histone-2B RNA interference (RNAi) for genetic ablation of neoblast cells in Schmidtea mediterranea as an alternative to irradiation. We characterize the rapid, neoblast-specific phen...
We present pipeComp (https://​github.​com/​plger/​pipeComp), a flexible R framework for pipeline comparison handling interactions between analysis steps and relying on...
APA can be profiled using a number of established computational tools that infer polyadenylation sites from standard, short-read RNA-seq datasets. Here, we benchmarked a number ... DaPars2, GETUTR, and APATrap— a...
RNA processing, including splicing and alternative polyadenylation, is crucial to gene function and regulation, but methods to detect RNA processing from single-cell RNA sequencing data are limited by reliance...
Calling fusion genes from RNA-seq data is well established, but other transcriptional ... developed MINTIE, an integrated pipeline for RNA-seq data. We take a reference-free approach...
Mammalian cells have three types of RNA polymerases (Pols), Pol I, II, and III. However, the extent to which these polymerases are cross-regulated and the underlying mechanisms remain unclear.
We introduce CellPhy, a maximum likelihood framework for inferring phylogenetic trees from somatic single-cell single-nucleotide variants. CellPhy leverages a finite-site Markov genotype model with 16 diploid ...
In comparative high-throughput sequencing assays, a fundamental task is the analysis of count data, such as read counts per gene in RNA-seq, for evidence of systematic changes across experimental...DESeq2, a meth...
Standard preprocessing of single-cell RNA-seq UMI data includes normalization by sequencing depth...
scRNA-seq dataset integration occurs in different contexts, such...
Gene expression profiling is being widely applied in cancer research to identify biomarkers for clinical endpoint prediction. Since RNA-seq provides a powerful tool for transcriptome-based ... sought to systemati...
Gene annotations, such as those in GENCODE, are derived primarily from alignments of spliced cDNA sequences and protein sequences. The impact of RNA-seq data on annotation has been confined to...
A large number of computational methods have been developed for analyzing differential gene expression in RNA-seq data. We describe a comprehensive evaluation of ... note that array-based methods adapted to RNA-seq
The Erratum to this article has been published in Genome Biology 2015 16:261
As many methods for quantifying isoform abundance with comparable accuracy are available, a user’s choice will likely be determined by factors such as the memory and runtime requirements, as well as the availabil...
scRNA-seq profiles each represent a highly partial sample ... . We describe a methodology for partitioning scRNA-seq datasets into metacells: disjoint and homogenous groups of profiles that could have been resamp...
VirtUaL ChIP-seq Analysis through Networks (VULCAN) infers regulatory ... from publicly available tumor expression data onto ChIP-seq data. We apply our method to dissect...
The Correction to this article has been published in Genome Biology 2019 20:122
Single-cell RNA sequencing (scRNA-seq) offers new opportunities to study gene expression ... better accuracy than other six publicly available scRNA-seq imputation methods on experimental data, as measured ... to...
Single-cell RNA-sequencing (scRNA-seq) allows studying heterogeneity in gene expression in ... without annotation. In applications to multiple scRNA-seq datasets, we find that f-scLVM robustly decomposes scRNA-seq
We introduce a k...-mer-based computational protocol, DE-kupl, for capturing local RNA variation in a set of RNA-seq libraries, independently of a reference genome or...k...-mers with differential abundance direc...
Spatial mapping of genomic data to tissue context in a high-throughput and high-resolution manner has been challenging due to technical limitations. Here, we describe PHLI-seq, a novel approach that enables high-...
CLIP-seq methods allow the generation of genome-wide ... However, due to differences between different CLIP-seq assays, existing computational approaches to analyze the ... elements in RNAs from data of all CLIP-
We describe a highly sensitive, quantitative, and inexpensive technique for targeted sequencing of transcript cohorts or genomic regions from thousands of bulk samples or single cells in parallel. Multiplexing is...
Methods for the analysis of chromatin immunoprecipitation sequencing (ChIP-seq) data start by aligning the short reads...de novo analysis of ChIP-seq data. Our methods combine de novo assembly with statistical te...
Obtaining RNA-seq measurements involves a complex data analytical process...http://​bioconductor.​org/​packages/​rnaseqcomp). Using two independent datasets, we ...
The Erratum to this article has been published in Genome Biology 2016 17:203
The Erratum to this article has been published in Genome Biology 2016 17:107
Epitranscriptome profiling using MeRIP-seq is a powerful technique for in vivo ... tool for detecting differentially methylated loci in MeRIP-seq data. RADAR enables accurate identification of altered...
Micrococcal nuclease (MNase) is widely used to map nucleosomes. However, its aggressive endo-/exo-nuclease activities make MNase-seq unreliable for determining nucleosome occupancies, because cleavages...Drosophi...
We present a new de novo transcriptome assembler, Bridger, which takes advantage of techniques employed in Cufflinks to overcome limitations of the existing de novo...assemblers. When tested on dog, human, and mo...
Recent innovations in single-cell Assay for Transposase Accessible Chromatin using sequencing (scATAC-seq) enable profiling of the epigenetic landscape of thousands of individual cells. scATAC-seq data analysis p...
Single-cell RNA-Seq (scRNA-Seq) profiles gene expression of individual cells. Recent scRNA-Seq datasets have incorporated unique molecular identifiers (UMIs...
The Correction to this article has been published in Genome Biology 2020 21:179
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