ArticleNucleic acids research2012
RNASEQR--a streamlined and accurate RNA-seq sequence analysis program.
Article in Nucleic acids research, 2012. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 29 citations in OpenAlex.
- GAiN: An integrative tool utilizing generative adversarial neural networks for augmented gene expression analysis.Patterns (New York, N.Y.) · 2024Article
- Systems Biology Approaches to Decipher the Underlying Molecular Mechanisms of Glioblastoma Multiforme.International journal of molecular sciences · 2021Review
- ARMT: An automatic RNA-seq data mining tool based on comprehensive and integrative analysis in cancer research.Computational and structural biotechnology journal · 2021Article
- Olfactory Receptors as Biomarkers in Human Breast Carcinoma Tissues.Frontiers in oncology · 2018Article
- Low-cost, Low-bias and Low-input RNA-seq with High Experimental Verifiability based on Semiconductor Sequencing.Scientific reports · 2017Article
- PARRoT- a homology-based strategy to quantify and compare RNA-sequencing from non-model organisms.BMC bioinformatics · 2016Article
- A comprehensive next generation sequencing-based virome assessment in brain tissue suggests no major virus - tumor association.Acta neuropathologica communications · 2016Article
- Identification of allelic expression imbalance genes in human hepatocellular carcinoma through massively parallel DNA and RNA sequencing.Medical oncology (Northwood, London, England) · 2016Article
- RNA-Seq identifies key reproductive gene expression alterations in response to cadmium exposure.BioMed research international · 2014Article
- Reliable identification of genomic variants from RNA-seq data.American journal of human genetics · 2013Article
- Mining RNA-seq data for infections and contaminations.PloS one · 2013Article
- DBATE: database of alternative transcripts expression.Database : the journal of biological databases and curation · 2013Article
- A context-based approach to identify the most likely mapping for RNA-seq experiments.BMC bioinformatics · 2012Article
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
9 authors at 4 institutions in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Next-generation sequencing (NGS) technologies-based transcriptomic profiling method often called RNA-seq has been widely used to study global gene expression, alternative exon usage, new exon discovery, novel transcriptional isoforms and genomic sequence variations. However, this technique also poses many biological and informatics challenges to extracting meaningful biological information. The RNA-seq data analysis is built on the foundation of high quality initial genome localization and alignment information for RNA-seq sequences. Toward this goal, we have developed RNASEQR to accurately and effectively map millions of RNA-seq sequences. We have systematically compared RNASEQR with four of the most widely used tools using a simulated data set created from the Consensus CDS project and two experimental RNA-seq data sets generated from a human glioblastoma patient. Our results showed that RNASEQR yields more accurate estimates for gene expression, complete gene structures and new transcript isoforms, as well as more accurate detection of single nucleotide variants (SNVs). RNASEQR analyzes raw data from RNA-seq experiments effectively and outputs results in a manner that is compatible with a wide variety of specialized downstream analyses on desktop computers.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
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.