ArticleBioinformatics (Oxford, England)2011
RSEQtools: a modular framework to analyze RNA-Seq data using compact, anonymized data summaries.
Article in Bioinformatics (Oxford, England), 2011. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 78 papers, 1 of them a synthesis that pooled it.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
78 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Ewing sarcoma with ERG gene rearrangements: A molecular study focusing on the prevalence of FUS-ERG and common pitfalls in detecting EWSR1-ERG fusions by FISH.Genes, chromosomes & cancer · 2016Pooled it
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- RNAdetector: a free user-friendly stand-alone and cloud-based system for RNA-Seq data analysis.BMC bioinformatics · 2021Article
- Single-cell transcriptional changes associated with drug tolerance and response to combination therapies in cancer.Nature communications · 2021Article
- Role of Transposable Elements in Gene Regulation in the Human Genome.Life (Basel, Switzerland) · 2021Review
- Role of specialized composition of SWI/SNF complexes in prostate cancer lineage plasticity.Nature communications · 2020Article
- Cortical morphology at birth reflects spatiotemporal patterns of gene expression in the fetal human brain.PLoS biology · 2020Article
- Integrative multiplatform molecular profiling of benign prostatic hyperplasia identifies distinct subtypes.Nature communications · 2020Article
- CHD1 Loss Alters AR Binding at Lineage-Specific Enhancers and Modulates Distinct Transcriptional Programs to Drive Prostate Tumorigenesis.Cancer cell · 2019Article
- Human neuroepithelial stem cell regional specificity enables spinal cord repair through a relay circuit.Nature communications · 2018Article
- Marked Diversity of Unique Cortical Enhancers Enables Neuron-Specific Tools by Enhancer-Driven Gene Expression.Current biology : CB · 2018Article
- SPAR: small RNA-seq portal for analysis of sequencing experiments.Nucleic acids research · 2018Article
- Analysis of sensitive information leakage in functional genomics signal profiles through genomic deletions.Nature communications · 2018Article
18 more citing papers are in PubMed but not listed here.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
summaryThe advent of next-generation sequencing for functional genomics has given rise to quantities of sequence information that are often so large that they are difficult to handle. Moreover, sequence reads from a specific individual can contain sufficient information to potentially identify and genetically characterize that person, raising privacy concerns. In order to address these issues, we have developed the Mapped Read Format (MRF), a compact data summary format for both short and long read alignments that enables the anonymization of confidential sequence information, while allowing one to still carry out many functional genomics studies. We have developed a suite of tools (RSEQtools) that use this format for the analysis of RNA-Seq experiments. These tools consist of a set of modules that perform common tasks such as calculating gene expression values, generating signal tracks of mapped reads and segmenting that signal into actively transcribed regions. Moreover, the tools can readily be used to build customizable RNA-Seq workflows. In addition to the anonymization afforded by MRF, this format also facilitates the decoupling of the alignment of reads from downstream analyses. AVAILABILITY AND IMPLEMENTATION: RSEQtools is implemented in C and the source code is available at http://rseqtools.gersteinlab.org/.
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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.