Probabilistic error correction for RNA sequencing
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Summary
Using human RNA-Seq data, it is shown that SEECER greatly improves on previous methods in terms of quality of read alignment to the genome and assembly accuracy, and is the first to successfully address read error correction problems in Rna-seq data.
- Type
- article
- Published
- 2013-04-03
- Cited by
- 113
- References
- 56
- Access
- Open access
- OpenAlex
- https://openalex.org/W2009735916
- Semantic Scholar
- https://api.semanticscholar.org/CorpusID:4535158
Keywords
Biology, Computational biology, RNA-Seq, Transcriptome, DNA sequencing
References
- Transcriptome Sequencing and Characterization for the Sea Cucumber Apostichopus japonicus (Selenka, 1867)
- ECHO: a reference-free short-read error correction algorithm.
- RNA-Seq: a revolutionary tool for transcriptomics
- Streaming fragment assignment for real-time analysis of sequencing experiments
- RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome
- Online EM for Unsupervised Models
- ConDeTri - A Content Dependent Read Trimmer for Illumina Data
- Modeling non-uniformity in short-read rates in RNA-Seq data
- Phylogenetic relationships among extant classes of echinoderms, as inferred from sequences of 18S rDNA, coincide with relationships deduced from the fossil record
- SeqAn An efficient, generic C++ library for sequence analysis
- Prediction of alternative isoforms from exon expression levels in RNA-Seq experiments
- NCBI GEO: archive for functional genomics data sets—10 years on
- New tools and methods for direct programmatic access to the dbSNP relational database
- A fast, lock-free approach for efficient parallel counting of occurrences of k-mers
- A Global View of Gene Activity and Alternative Splicing by Deep Sequencing of the Human Transcriptome
- A survey of error-correction methods for next-generation sequencing
- A comprehensive comparison of RNA-Seq-based transcriptome analysis from reads to differential gene expression and cross-comparison with microarrays: a case study in Saccharomyces cerevisiae
- De novo assembly and analysis of RNA-seq data
- Transcript length bias in RNA-seq data confounds systems biology
- Efficient frequency-based de novo short-read clustering for error trimming in next-generation sequencing.
Cited by
- Probabilistic Models for Collecting, Analyzing, and Modeling Expression Data
- VDR hypermethylation and HIV‐induced T cell loss
- Karect: accurate correction of substitution, insertion and deletion errors for next-generation sequencing data
- Combined cultivation and single-cell approaches to the phylogenomics of nucleariid amoebae, close relatives of fungi
- Crossing the streams: a framework for streaming analysis of short DNA sequencing reads
- Bermuda: Bidirectional de novo assembly of transcripts with new insights for handling uneven coverage
- Epigenetic Modulation of Human Podocyte Vitamin D Receptor in HIV milieu
- Microfluidics: reframing biological enquiry
- Marginalizing Corrupted Features
- nagnag: Identification and quantification of NAGNAG alternative splicing using RNA‐Seq data
- Denoising DNA deep sequencing data—high-throughput sequencing errors and their correction
- Fuelling genetic and metabolic exploration of C3 bioenergy crops through the first reference transcriptome of Arundo donax L.
- Non-random DNA fragmentation in next-generation sequencing
- Bermuda: de novo assembly of transcripts with new insights for handling uneven coverage
- Improving transcriptome assembly through error correction of high-throughput sequence reads
- Comparison of RNA-Seq and Microarray in Transcriptome Profiling of Activated T Cells
- Phylogenomic Analyses of Echinodermata Support the Sister Groups of Asterozoa and Echinozoa
- A glance at quality score: implication for de novo transcriptome reconstruction of Illumina reads
- Prevention, diagnosis and treatment of high‐throughput sequencing data pathologies
- Rcorrector: efficient and accurate error correction for Illumina RNA-seq reads
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