Tag Archives: transcriptome assembly

CLASS – Splice Variant Annotation from RNA-Seq Reads

rna-seq

Next generation sequencing of cellular RNA is making it possible to characterize genes and alternative splicing in unprecedented detail. However, designing bioinformatics tools to capture splicing variation accurately has proven difficult. Current programs find major isoforms of a gene but ...

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Bayesembler – bayesian transcriptome assembly

RNA-seq allows for simultaneous transcript discovery and quantification, but reconstructing complete transcripts from such data remains difficult. Here, researchers from the University of Copenhagen introduce the Bayesembler, a novel probabilistic method for transcriptome assembly built on a Bayesian model of ...

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A Comparison of Next Generation Sequencing Technologies for Transcriptome Assembly

De novo assembled transcriptomes, in combination with RNA-Seq, are powerful tools to explore gene sequence and expression level in organisms without reference genomes. Investigators must first choose which high throughput sequencing platforms will provide data most suitable for their experimental ...

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RNA-Seq Assembly – Fundamental Limits, Algorithms and Software

rna-seq

David Tse – Stanford University Symposium on Turbo Codes and Iterative Information Processing Bremen, Germany August 20, 2014 Joint work with Sreeram Kannan and Lior Pachter. Research supported by NSF Center for Science of Information

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Tutorial – Intermediate RNA-Seq: Tips, Tricks and Non-Human Organisms

rna-seq

Minnesota Supercomputing Institute Date: Thursday, September 25, 2014, 01:00 pm – 03:00 pm Location: Room 105 Cargill Building This lecture will go over more advanced RNA-Seq topics and compliments Basics of RNA-seq. Lecture Topics: Non-mammal specific RNA-Seq issues Transcriptome assembly ...

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RNA-seq analysis 3 day workshop

rna-seq

Next date: 24.03.2014 – 26.03.2014. Location: Oslo, Norway This introductory level course is focused on experimental design, differential expression analysis and transcriptome assembly using R/Bioconductor and open-source tools. Hands-on analysis exercises will be based on real world data – bring ...

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