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We are analyzing https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-12-323.

Title:
RSEM: accurate transcript quantification from RNA-Seq data with or without a reference genome | BMC Bioinformatics | Full Text
Description:
Background RNA-Seq is revolutionizing the way transcript abundances are measured. A key challenge in transcript quantification from RNA-Seq data is the handling of reads that map to multiple genes or isoforms. This issue is particularly important for quantification with de novo transcriptome assemblies in the absence of sequenced genomes, as it is difficult to determine which transcripts are isoforms of the same gene. A second significant issue is the design of RNA-Seq experiments, in terms of the number of reads, read length, and whether reads come from one or both ends of cDNA fragments. Results We present RSEM, an user-friendly software package for quantifying gene and isoform abundances from single-end or paired-end RNA-Seq data. RSEM outputs abundance estimates, 95% credibility intervals, and visualization files and can also simulate RNA-Seq data. In contrast to other existing tools, the software does not require a reference genome. Thus, in combination with a de novo transcriptome assembler, RSEM enables accurate transcript quantification for species without sequenced genomes. On simulated and real data sets, RSEM has superior or comparable performance to quantification methods that rely on a reference genome. Taking advantage of RSEM
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Keywords {🔍}

reads, data, rsem, rnaseq, transcript, read, gene, pubmed, quantification, set, methods, model, estimates, abundance, article, genome, number, length, google, scholar, quality, reference, isoform, genes, file, transcripts, sequencing, fragment, accuracy, alignments, distribution, central, abundances, error, values, refseq, additional, ensembl, results, sequences, parameters, cas, simulated, sets, cufflinks, accurate, experiments, alignment, original, simulation,

Topics {✒️}

user-friendly scripts rsem-prepare-reference rna-seq-based transcript quantitation rsem-calculate-expression script handles conserved multi-exonic structure nih grant 1r01hg005232-01a1 paired-end rna-seq data full-length transcriptome assembly taqman qrt-pcr measurements including taqman qrt-pcr full size image rna-seq data generation rna-seq libraries generated bmc bioinformatics 2010 bmc bioinformatics 12 allocating ambiguous short-reads simulate rna-seq data raw rna-seq reads maqc rna-seq data rna-seq data sets real rna-seq data se rna-seq protocols position-specific bias correction user-friendly software package sequenced rna-seq fragment rna-seq abundance predictions authors scientific editing simulated rna-seq data rna-seq data set user-friendly software tool color-space reads generated privacy choices/manage cookies ucsc wig-formatted file maqc rna-seq samples generated rna-seq data global isoform-level estimates reference preparation script cell type-specific transcriptomes modeling rna-seq data probabilistically-weighted read alignments kent wj se rna-seq analysis rna-seq quantification methods article li gtf-formatted annotation file background rna-seq gene-level abundance estimates rsem-simulate-reads program position-dependent error model short single-end reads hansen kd

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