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Aligner

The Experts below are selected from a list of 842019 Experts worldwide ranked by ideXlab platform

Thomas L Madden – 1st expert on this subject based on the ideXlab platform

  • magic blast an accurate rna seq Aligner for long and short reads
    BMC Bioinformatics, 2019
    Co-Authors: Grzegorz M Boratyn, Jean Thierrymieg, Danielle Thierrymieg, Ben Busby, Thomas L Madden

    Abstract:

    Next-generation sequencing technologies can produce tens of millions of reads, often paired-end, from transcripts or genomes. But few programs can align RNA on the genome and accurately discover introns, especially with long reads. We introduce Magic-BLAST, a new Aligner based on ideas from the Magic pipeline. Magic-BLAST uses innovative techniques that include the optimization of a spliced alignment score and selective masking during seed selection. We evaluate the performance of Magic-BLAST to accurately map short or long sequences and its ability to discover introns on real RNA-seq data sets from PacBio, Roche and Illumina runs, and on six benchmarks, and compare it to other popular Aligners. Additionally, we look at alignments of human idealized RefSeq mRNA sequences perfectly matching the genome. We show that Magic-BLAST is the best at intron discovery over a wide range of conditions and the best at mapping reads longer than 250 bases, from any platform. It is versatile and robust to high levels of mismatches or extreme base composition, and reasonably fast. It can align reads to a BLAST database or a FASTA file. It can accept a FASTQ file as input or automatically retrieve an accession from the SRA repository at the NCBI.

  • magic blast an accurate dna and rna seq Aligner for long and short reads
    bioRxiv, 2018
    Co-Authors: Grzegorz M Boratyn, Jean Thierrymieg, Danielle Thierrymieg, Ben Busby, Thomas L Madden

    Abstract:

    Next-generation sequencing technologies can produce tens of millions of reads, often paired-end, from transcripts or genomes. But few programs can align RNA on the genome and accurately discover introns, especially with long reads. To address these issues, we introduce Magic-BLAST, a new Aligner based on ideas from the Magic pipeline. It uses innovative techniques that include the optimization of a spliced alignment score and selective masking during seed selection. We evaluate the performance of Magic-BLAST to accurately map short or long sequences and its ability to discover introns on real RNA-seq data sets from PacBio, Roche and Illumina runs, and on six benchmarks, and compare it to other popular Aligners. Additionally, we look at alignments of human idealized RefSeq mRNA sequences perfectly matching the genome. We show that Magic-BLAST is the best at intron discovery over a wide range of conditions. It is versatile and robust to high levels of mismatches or extreme base composition and works well with very long reads. It is reasonably fast. It can align reads to a BLAST database or a FASTA file. It can accept a FASTQ file as input or automatically retrieve an accession from the SRA repository at the NCBI.

Shuichi Matsuda – 2nd expert on this subject based on the ideXlab platform

  • kinematic alignment produces near normal knee motion but increases contact stress after total knee arthroplasty a case study on a single implant design
    Knee, 2015
    Co-Authors: Masahiro Ishikawa, Shinichi Kuriyama, Moritoshi Furu, Shinichiro Nakamura, Shuichi Matsuda

    Abstract:

    Abstract Background Kinematically aligned total knee arthroplasty (TKA) is of increasing interest because this method might improve postoperative patient satisfaction. In kinematic alignment the femoral component is implanted in a slightly more valgus and internally rotated position, and the tibial component is implanted in a slightly more varus and internally rotated position, than in mechanical alignment. However, the biomechanics of kinematically aligned TKA remain largely unknown. The aim of this study was to compare the kinematics and contact stresses of mechanically and kinematically aligned TKAs. Methods A musculoskeletal computer simulation was used to determine the effects of mechanically or kinematically aligned TKA. Knee kinematics were examined for mechanically aligned, kinematically aligned, and kinematically aligned outlier models. Patellofemoral and tibiofemoral contact forces were measured using finite element analysis. Results Greater femoral rollback and more external rotation of the femoral component were observed with kinematically aligned TKA than mechanically aligned TKA. However, patellofemoral and tibiofemoral contact stresses were increased in kinematically aligned TKA. Conclusions These findings suggest that kinematically aligned TKA produces near-normal knee kinematics, but that concerns for long-term outcome might arise because of high contact stresses.

Grzegorz M Boratyn – 3rd expert on this subject based on the ideXlab platform

  • magic blast an accurate rna seq Aligner for long and short reads
    BMC Bioinformatics, 2019
    Co-Authors: Grzegorz M Boratyn, Jean Thierrymieg, Danielle Thierrymieg, Ben Busby, Thomas L Madden

    Abstract:

    Next-generation sequencing technologies can produce tens of millions of reads, often paired-end, from transcripts or genomes. But few programs can align RNA on the genome and accurately discover introns, especially with long reads. We introduce Magic-BLAST, a new Aligner based on ideas from the Magic pipeline. Magic-BLAST uses innovative techniques that include the optimization of a spliced alignment score and selective masking during seed selection. We evaluate the performance of Magic-BLAST to accurately map short or long sequences and its ability to discover introns on real RNA-seq data sets from PacBio, Roche and Illumina runs, and on six benchmarks, and compare it to other popular Aligners. Additionally, we look at alignments of human idealized RefSeq mRNA sequences perfectly matching the genome. We show that Magic-BLAST is the best at intron discovery over a wide range of conditions and the best at mapping reads longer than 250 bases, from any platform. It is versatile and robust to high levels of mismatches or extreme base composition, and reasonably fast. It can align reads to a BLAST database or a FASTA file. It can accept a FASTQ file as input or automatically retrieve an accession from the SRA repository at the NCBI.

  • magic blast an accurate dna and rna seq Aligner for long and short reads
    bioRxiv, 2018
    Co-Authors: Grzegorz M Boratyn, Jean Thierrymieg, Danielle Thierrymieg, Ben Busby, Thomas L Madden

    Abstract:

    Next-generation sequencing technologies can produce tens of millions of reads, often paired-end, from transcripts or genomes. But few programs can align RNA on the genome and accurately discover introns, especially with long reads. To address these issues, we introduce Magic-BLAST, a new Aligner based on ideas from the Magic pipeline. It uses innovative techniques that include the optimization of a spliced alignment score and selective masking during seed selection. We evaluate the performance of Magic-BLAST to accurately map short or long sequences and its ability to discover introns on real RNA-seq data sets from PacBio, Roche and Illumina runs, and on six benchmarks, and compare it to other popular Aligners. Additionally, we look at alignments of human idealized RefSeq mRNA sequences perfectly matching the genome. We show that Magic-BLAST is the best at intron discovery over a wide range of conditions. It is versatile and robust to high levels of mismatches or extreme base composition and works well with very long reads. It is reasonably fast. It can align reads to a BLAST database or a FASTA file. It can accept a FASTQ file as input or automatically retrieve an accession from the SRA repository at the NCBI.