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Cole Trapnell

Researcher at University of Washington

Publications -  148
Citations -  101469

Cole Trapnell is an academic researcher from University of Washington. The author has contributed to research in topics: Biology & Gene. The author has an hindex of 57, co-authored 123 publications receiving 84590 citations. Previous affiliations of Cole Trapnell include Iowa State University & Massachusetts Institute of Technology.

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Ultrafast and memory-efficient alignment of short DNA sequences to the human genome

TL;DR: Bowtie extends previous Burrows-Wheeler techniques with a novel quality-aware backtracking algorithm that permits mismatches and can be used simultaneously to achieve even greater alignment speeds.
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Transcript assembly and quantification by RNA-Seq reveals unannotated transcripts and isoform switching during cell differentiation

TL;DR: The results suggest that Cufflinks can illuminate the substantial regulatory flexibility and complexity in even this well-studied model of muscle development and that it can improve transcriptome-based genome annotation.
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TopHat: discovering splice junctions with RNA-Seq

TL;DR: The TopHat pipeline is much faster than previous systems, mapping nearly 2.2 million reads per CPU hour, which is sufficient to process an entire RNA-Seq experiment in less than a day on a standard desktop computer.
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TopHat2: accurate alignment of transcriptomes in the presence of insertions, deletions and gene fusions

TL;DR: TopHat2 is described, which incorporates many significant enhancements to TopHat, and combines the ability to identify novel splice sites with direct mapping to known transcripts, producing sensitive and accurate alignments, even for highly repetitive genomes or in the presence of pseudogenes.
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Differential gene and transcript expression analysis of RNA-seq experiments with TopHat and Cufflinks

TL;DR: This protocol begins with raw sequencing reads and produces a transcriptome assembly, lists of differentially expressed and regulated genes and transcripts, and publication-quality visualizations of analysis results, which takes less than 1 d of computer time for typical experiments and ∼1 h of hands-on time.