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10.1186/s13015-015-0062-4 http://scihub22266oqcxt.onion/10.1186/s13015-015-0062-4 C4688996!4688996!26702294     free     free     free Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534 Deprecated: Implicit conversion from float 215.6 to int loses precision in C:\Inetpub\vhosts\kidney.de\httpdocs\pget.php on line 534       Algorithms+Mol+Biol 2015 ; 10 (ä): ä Nephropedia Template TP {{tp|p=26702294|t=2015. HIA: a genome mapper using hybrid index-based sequence alignment |pdf=|usr=}}{{26702294}} gab.com Text HIA: a genome mapper using hybrid index-based sequence alignment JO: Algorithms Mol Biol http://www.kidney.de/pget.php?&tw=1&pmid=26702294 #FOAvip Background: A number of alignment tools have been developed to align sequencing reads to the human reference genome. The scale of information from next-generation sequencing (NGS) experiments, however, is increasing rapidly. Recent studies based on NGS technology have routinely produced exome or whole-genome sequences from several hundreds or thousands of samples. To accommodate the increasing need of analyzing very large NGS data sets, it is necessary to develop faster, more sensitive and accurate mapping tools. Results: HIA uses two indices, a hash table index and a suffix array index. The hash table performs direct lookup of a q-gram, and the suffix array performs very fast lookup of variable-length strings by exploiting binary search. We observed that combining hash table and suffix array (hybrid index) is much faster than the suffix array method for finding a substring in the reference sequence. Here, we defined the matching region (MR) is a longest common substring between a reference and a read. And, we also defined the candidate alignment regions (CARs) as a list of MRs that is close to each other. The hybrid index is used to find candidate alignment regions (CARs) between a reference and a read. We found that aligning only the unmatched regions in the CAR is much faster than aligning the whole CAR. In benchmark analysis, HIA outperformed in mapping speed compared with the other aligners, without significant loss of mapping accuracy. Conclusions: Our experiments show that the hybrid of hash table and suffix array is useful in terms of speed for mapping NGS sequencing reads to the human reference genome sequence. In conclusion, our tool is appropriate for aligning massive data sets generated by NGS sequencing. Electronic supplementary material: The online version of this article (doi:10.1186/s13015-015-0062-4) contains supplementary material, which is available to authorized users. Twit Text FOAVip HIA: a genome mapper using hybrid index-based sequence alignment ????Algorithms Mol Biol http://www.kidney.de/pget.php?&tw=1&pmid=26702294 #FOAvip Twit Text # Free Paper on # # # # # LINK http://www.kidney.de/pget.php?&tw=1&pmid=26702294 #FOAvip English Wikipedia <ref>{{Cite pmid|26702294}}</ref> HIA: a genome mapper using hybrid index-based sequence alignment #MMPMID26702294 Choi J; Park K; Cho SB; Chung M Algorithms Mol Biol 2015[]; 10 (ä): ä PMID26702294show ga Background: A number of alignment tools have been developed to align sequencing reads to the human reference genome. The scale of information from next-generation sequencing (NGS) experiments, however, is increasing rapidly. Recent studies based on NGS technology have routinely produced exome or whole-genome sequences from several hundreds or thousands of samples. To accommodate the increasing need of analyzing very large NGS data sets, it is necessary to develop faster, more sensitive and accurate mapping tools. Results: HIA uses two indices, a hash table index and a suffix array index. The hash table performs direct lookup of a q-gram, and the suffix array performs very fast lookup of variable-length strings by exploiting binary search. We observed that combining hash table and suffix array (hybrid index) is much faster than the suffix array method for finding a substring in the reference sequence. Here, we defined the matching region (MR) is a longest common substring between a reference and a read. And, we also defined the candidate alignment regions (CARs) as a list of MRs that is close to each other. The hybrid index is used to find candidate alignment regions (CARs) between a reference and a read. We found that aligning only the unmatched regions in the CAR is much faster than aligning the whole CAR. In benchmark analysis, HIA outperformed in mapping speed compared with the other aligners, without significant loss of mapping accuracy. Conclusions: Our experiments show that the hybrid of hash table and suffix array is useful in terms of speed for mapping NGS sequencing reads to the human reference genome sequence. In conclusion, our tool is appropriate for aligning massive data sets generated by NGS sequencing. Electronic supplementary material: The online version of this article (doi:10.1186/s13015-015-0062-4) contains supplementary material, which is available to authorized users. äHIA: a genome mapper using hybrid index-based sequence alignment (epmc).pdf DeepDyve Pubget Overpricing