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It maps reads to the reference genome with gapped alignment and scores these mappings with consideration for sequencing and alignment errors.
TopHat initially removes a portion of reads based on quality information accompanying each read, then maps reads to the reference genome.
TopHat maps reads to splice sites in a mammalian genome at a rate of ∼2.2 million reads per CPU hour.
Thus this second class of apparent rearrangements are where an aligner confidently maps reads to the 3' end or polyA of a mobile element in the reference genome.
The main new contributions of our work are the following: (i) we introduce the concept of a linear reference multi-genome that incorporates the catalogue of all known genomic variants with a reference genome (e.g. SNPs, insertions, deletions and inversions), and (ii) we develop a BWT-based read alignment algorithm, BWBBLE, that accurately maps reads to this multi-genome.
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Hence, neither Bowtie nor MAQ should be used for mapping reads to quantify gene expression.
Gene expression profiling was measured by mapping reads to assembled sequences using SOAP [66].
One further limitation of Bowtie and MAQ is the random assignment of equally well mapped reads to the corresponding genes.
Tools for analyzing RNA-Seq data include TopHat [7], which analyzes mapped reads to identify splice junctions between exons.
We therefore assembled the mapped reads to obtain 19,752 NTRs.
Therefore, mapping reads to a reference genome has two limitations.
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