Sentence examples for sensitive alignment from inspiring English sources

Seed-and-extend methods break reads into seeds which are mapped to the genome, and much like seed-based unspliced aligners, candidate mapping locations are examined with more sensitive alignment methods.

In most cases, half or more of the bases in the available ENCODE sequences were in alignment with the 2× assemblies (fractions ranged from 38 84%), indicating good coverage in the 2× assemblies and a reasonably sensitive alignment procedure, despite the use of conservative filters.

Significant improvements can be observed for both simple (GOTOH) and the most sensitive alignment methods (HHALIGN).

Such features facilitate sensitive alignment of non-human primate RNA-Seq data to a human reference.

Thirdly, genome scale, highly sensitive alignment, variant calling, and annotation are now possible in less than 1 h.

The results from the VISTA database were not as clear when the less sensitive alignment method was employed.

Original alignment tools such as BLAST (Altschul et al., 1990) and BLAT (Kent, 2002), are capable of finding highly sensitive alignments for long reads, but do not provide full sensitivity to specific numbers of mismatches and are incapable of efficiently mapping the amount of reads currently produced by short-read sequencing machines.

This high level of performance enables computation of extremely large numbers of highly sensitive alignments in dramatically reduced time, and is complementary to new BWT-based aligners that excel at quickly reporting a small number of alignments per read.

Our results on simulated data let us expect an even higher performance for more sensitive alignments and appropriate multi-mapper handling.

Although PerM and Bowtie both index the genome, PerM finds full sensitive alignments through seed subsequence matching while Bowtie uses a modified exact matching algorithm and quality-aware backtracking to report alignments.

It uses the Hadoop implementation of MapReduce to efficiently execute in parallel on multiple compute nodes, thus making it feasible to perform highly sensitive alignments on large read sets.