We are analyzing https://link.springer.com/article/10.1186/gb-2012-13-1-r4.

Title:
SpliceGrapher: detecting patterns of alternative splicing from RNA-Seq data in the context of gene models and EST data | Genome Biology
Description:
We propose a method for predicting splice graphs that enhances curated gene models using evidence from RNA-Seq and EST alignments. Results obtained using RNA-Seq experiments in Arabidopsis thaliana show that predictions made by our SpliceGrapher method are more consistent with current gene models than predictions made by TAU and Cufflinks. Furthermore, analysis of plant and human data indicates that the machine learning approach used by SpliceGrapher is useful for discriminating between real and spurious splice sites, and can improve the reliability of detection of alternative splicing. SpliceGrapher is available for download at http://SpliceGrapher.sf.net .
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28 years and 1 months (reg. 1997-05-29).

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Keywords {🔍}

splice, splicegrapher, data, gene, pubmed, exon, rnaseq, reads, article, alignments, exons, site, google, scholar, junctions, alternative, events, models, intron, sites, graph, junction, cas, splicing, read, figure, predictions, cufflinks, annotations, predicted, est, alignment, evidence, thaliana, acceptor, shortread, tau, sequences, donor, central, additional, file, graphs, genome, sequence, spliced, length, genes, table, tophat,

Topics {✒️}

arabidopsis serine/arginine-rich proteins current-generation high-throughput sequencing short-read spliced-alignment programs serine/arginine-rich proteins article number r4 supersplat-spliced rna-seq alignment asa ben-hur article download pdf gc-ag splice-site dimers short-read coverage remains integrate rna-seq data short-read sequence data rna-seq read coverage including rna-seq reads conserved multi-exonic structure rna-seq alignment data full-length transcriptome assembly rna-seq read alignments perform short-read alignments incorporate rna-seq data rna-seq spliced alignments sequence alignment/map format accepting splice-junction alignments rna-seq exonic alignments interpret short-read data additional rna-seq data combining rna-seq data high-throughput sequencing short-read exon falls ungapped short-read alignments false-positive splice site short-read exon overlaps 1186/gb-2009-10-3-r25 splice-junction anchor regions human rna-seq data methods rna-seq data privacy choices/manage cookies junction-crossing reads align deep sequencing thaliana rna-seq data generation dna sequencing gc-ag splice sites splicegrapher includes modules full size image read depth remains receiver operating characteristic detects intron retention supersplat performs alignment expressed sequence tags machine learning approach

Schema {🗺️}

WebPage:
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         headline:SpliceGrapher: detecting patterns of alternative splicing from RNA-Seq data in the context of gene models and EST data
         description:We propose a method for predicting splice graphs that enhances curated gene models using evidence from RNA-Seq and EST alignments. Results obtained using RNA-Seq experiments in Arabidopsis thaliana show that predictions made by our SpliceGrapher method are more consistent with current gene models than predictions made by TAU and Cufflinks. Furthermore, analysis of plant and human data indicates that the machine learning approach used by SpliceGrapher is useful for discriminating between real and spurious splice sites, and can improve the reliability of detection of alternative splicing. SpliceGrapher is available for download at http://SpliceGrapher.sf.net .
         datePublished:2012-01-31T00:00:00Z
         dateModified:2012-01-31T00:00:00Z
         pageStart:1
         pageEnd:17
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            Acceptor Site
            Splice Junction
            Intron Retention
            Splice Graph
            Animal Genetics and Genomics
            Human Genetics
            Plant Genetics and Genomics
            Microbial Genetics and Genomics
            Bioinformatics
            Evolutionary Biology
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ScholarlyArticle:
      headline:SpliceGrapher: detecting patterns of alternative splicing from RNA-Seq data in the context of gene models and EST data
      description:We propose a method for predicting splice graphs that enhances curated gene models using evidence from RNA-Seq and EST alignments. Results obtained using RNA-Seq experiments in Arabidopsis thaliana show that predictions made by our SpliceGrapher method are more consistent with current gene models than predictions made by TAU and Cufflinks. Furthermore, analysis of plant and human data indicates that the machine learning approach used by SpliceGrapher is useful for discriminating between real and spurious splice sites, and can improve the reliability of detection of alternative splicing. SpliceGrapher is available for download at http://SpliceGrapher.sf.net .
      datePublished:2012-01-31T00:00:00Z
      dateModified:2012-01-31T00:00:00Z
      pageStart:1
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      keywords:
         Splice Site
         Acceptor Site
         Splice Junction
         Intron Retention
         Splice Graph
         Animal Genetics and Genomics
         Human Genetics
         Plant Genetics and Genomics
         Microbial Genetics and Genomics
         Bioinformatics
         Evolutionary Biology
      image:
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         name:Department of Computer Science, 1873 Campus Delivery, Colorado State University, Fort Collins, USA
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            address:
               name:Department of Computer Science, 1873 Campus Delivery, Colorado State University, Fort Collins, USA
               type:PostalAddress
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      name:Julie Thomas
      affiliation:
            name:Colorado State University
            address:
               name:Department of Biology and Program in Molecular Plant Biology, 1878 Campus Delivery, Colorado State University, Fort Collins, USA
               type:PostalAddress
            type:Organization
      name:Anireddy SN Reddy
      affiliation:
            name:Colorado State University
            address:
               name:Department of Biology and Program in Molecular Plant Biology, 1878 Campus Delivery, Colorado State University, Fort Collins, USA
               type:PostalAddress
            type:Organization
      name:Asa Ben-Hur
      affiliation:
            name:Colorado State University
            address:
               name:Department of Computer Science, 1873 Campus Delivery, Colorado State University, Fort Collins, USA
               type:PostalAddress
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            name:Colorado State University
            address:
               name:Department of Statistics, 1877 Campus Delivery, Colorado State University, Fort Collins, USA
               type:PostalAddress
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      name:Department of Computer Science, 1873 Campus Delivery, Colorado State University, Fort Collins, USA
      name:Department of Biology and Program in Molecular Plant Biology, 1878 Campus Delivery, Colorado State University, Fort Collins, USA
      name:Department of Biology and Program in Molecular Plant Biology, 1878 Campus Delivery, Colorado State University, Fort Collins, USA
      name:Department of Computer Science, 1873 Campus Delivery, Colorado State University, Fort Collins, USA
      name:Department of Statistics, 1877 Campus Delivery, Colorado State University, Fort Collins, USA

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