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We are analyzing https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-15-182.

Title:
Skewer: a fast and accurate adapter trimmer for next-generation sequencing paired-end reads | BMC Bioinformatics | Full Text
Description:
Background Adapter trimming is a prerequisite step for analyzing next-generation sequencing (NGS) data when the reads are longer than the target DNA/RNA fragments. Although typically used in small RNA sequencing, adapter trimming is also used widely in other applications, such as genome DNA sequencing and transcriptome RNA/cDNA sequencing, where fragments shorter than a read are sometimes obtained because of the limitations of NGS protocols. For the newly emerged Nextera long mate-pair (LMP) protocol, junction adapters are located in the middle of all properly constructed fragments; hence, adapter trimming is essential to gain the correct paired reads. However, our investigations have shown that few adapter trimming tools meet both efficiency and accuracy requirements simultaneously. The performances of these tools can be even worse for paired-end and/or mate-pair sequencing. Results To improve the efficiency of adapter trimming, we devised a novel algorithm, the bit-masked k-difference matching algorithm, which has O(k n) expected time with O(m) space, where k is the maximum number of differences allowed, n is the read length, and m is the adapter length. This algorithm makes it possible to fully enumerate all candidates that meet a specified threshold, e.g. error ratio, within a short period of time. To improve the accuracy of this algorithm, we designed a simple and easy-to-explain statistical scoring scheme to evaluate candidates in the pattern matching step. We also devised scoring schemes to fully exploit the paired-end/mate-pair information when it is applicable. All these features have been implemented in an industry-standard tool named Skewer ( https://sourceforge.net/projects/skewer ). Experiments on simulated data, real data of small RNA sequencing, paired-end RNA sequencing, and Nextera LMP sequencing showed that Skewer outperforms all other similar tools that have the same utility. Further, Skewer is considerably faster than other tools that have comparative accuracies; namely, one times faster for single-end sequencing, more than 12 times faster for paired-end sequencing, and 49% faster for LMP sequencing. Conclusions Skewer achieved as yet unmatched accuracies for adapter trimming with low time bound.
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Keywords {🔍}

adapter, reads, trimming, sequencing, data, algorithm, article, sequence, skewer, trimmers, read, additional, pubmed, google, scholar, file, number, matching, time, figure, processing, fragments, kdifference, table, lmp, quality, information, genome, adapters, tools, length, nextera, real, size, noted, authors, bmc, dna, roc, srna, trimmed, alignment, cutadapt, performance, stringency, pairedend, metrics, ngs, pattern, similar,

Topics {✒️}

paired-end/mate-pair information net/projects/skewer/files/simulator/ long-insert pe libraries k-difference matching algorithms semi-global sequence alignment author information authors paired-end rna sequencing full size image rna-seq-based transcriptomics flexible barcode demultiplexer extended k-difference problem mate-pair sequencing k-difference matching [4] authors scientific editing flexbar–flexible barcode finding approximate patterns fast gapped-read alignment data sets supporting bmc res notes processing paired-end reads refined dnase-seq protocol reverse-complementary counter-parts target dna/rna fragments high-throughput sequencing reads privacy choices/manage cookies transcriptome rna/cdna sequencing k-difference problem simulating adapter-contaminated reads processing single-end reads nextera lmp libraries k-difference constraint k-difference occurrences k-difference requirement recently published trimmers authors’ original file dynamic programming process references paired-end sequencing generation sequencing platforms long pe data page=trimmomatic fast bit-vector algorithm generation sequencing reads real sequencing data real data showed fragment size selection generation sequencing technologies dynamic programming matrix matching length increases nextera lmp reads

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WebPage:
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         description:Adapter trimming is a prerequisite step for analyzing next-generation sequencing (NGS) data when the reads are longer than the target DNA/RNA fragments. Although typically used in small RNA sequencing, adapter trimming is also used widely in other applications, such as genome DNA sequencing and transcriptome RNA/cDNA sequencing, where fragments shorter than a read are sometimes obtained because of the limitations of NGS protocols. For the newly emerged Nextera long mate-pair (LMP) protocol, junction adapters are located in the middle of all properly constructed fragments; hence, adapter trimming is essential to gain the correct paired reads. However, our investigations have shown that few adapter trimming tools meet both efficiency and accuracy requirements simultaneously. The performances of these tools can be even worse for paired-end and/or mate-pair sequencing. To improve the efficiency of adapter trimming, we devised a novel algorithm, the bit-masked k-difference matching algorithm, which has O(k n) expected time with O(m) space, where k is the maximum number of differences allowed, n is the read length, and m is the adapter length. This algorithm makes it possible to fully enumerate all candidates that meet a specified threshold, e.g. error ratio, within a short period of time. To improve the accuracy of this algorithm, we designed a simple and easy-to-explain statistical scoring scheme to evaluate candidates in the pattern matching step. We also devised scoring schemes to fully exploit the paired-end/mate-pair information when it is applicable. All these features have been implemented in an industry-standard tool named Skewer ( https://sourceforge.net/projects/skewer ). Experiments on simulated data, real data of small RNA sequencing, paired-end RNA sequencing, and Nextera LMP sequencing showed that Skewer outperforms all other similar tools that have the same utility. Further, Skewer is considerably faster than other tools that have comparative accuracies; namely, one times faster for single-end sequencing, more than 12 times faster for paired-end sequencing, and 49% faster for LMP sequencing. Skewer achieved as yet unmatched accuracies for adapter trimming with low time bound.
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      headline:Skewer: a fast and accurate adapter trimmer for next-generation sequencing paired-end reads
      description:Adapter trimming is a prerequisite step for analyzing next-generation sequencing (NGS) data when the reads are longer than the target DNA/RNA fragments. Although typically used in small RNA sequencing, adapter trimming is also used widely in other applications, such as genome DNA sequencing and transcriptome RNA/cDNA sequencing, where fragments shorter than a read are sometimes obtained because of the limitations of NGS protocols. For the newly emerged Nextera long mate-pair (LMP) protocol, junction adapters are located in the middle of all properly constructed fragments; hence, adapter trimming is essential to gain the correct paired reads. However, our investigations have shown that few adapter trimming tools meet both efficiency and accuracy requirements simultaneously. The performances of these tools can be even worse for paired-end and/or mate-pair sequencing. To improve the efficiency of adapter trimming, we devised a novel algorithm, the bit-masked k-difference matching algorithm, which has O(k n) expected time with O(m) space, where k is the maximum number of differences allowed, n is the read length, and m is the adapter length. This algorithm makes it possible to fully enumerate all candidates that meet a specified threshold, e.g. error ratio, within a short period of time. To improve the accuracy of this algorithm, we designed a simple and easy-to-explain statistical scoring scheme to evaluate candidates in the pattern matching step. We also devised scoring schemes to fully exploit the paired-end/mate-pair information when it is applicable. All these features have been implemented in an industry-standard tool named Skewer ( https://sourceforge.net/projects/skewer ). Experiments on simulated data, real data of small RNA sequencing, paired-end RNA sequencing, and Nextera LMP sequencing showed that Skewer outperforms all other similar tools that have the same utility. Further, Skewer is considerably faster than other tools that have comparative accuracies; namely, one times faster for single-end sequencing, more than 12 times faster for paired-end sequencing, and 49% faster for LMP sequencing. Skewer achieved as yet unmatched accuracies for adapter trimming with low time bound.
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         Adapter trimming
         Approximate string matching
         Local sequence alignment
         Barcode demultiplexing
         Bioinformatics
         Microarrays
         Computational Biology/Bioinformatics
         Computer Appl. in Life Sciences
         Algorithms
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      name:Institute of Plant Quarantine Research, Chinese Academy of Inspection and Quarantine, Beijing, China
      name:Institute of Plant Quarantine Research, Chinese Academy of Inspection and Quarantine, Beijing, China
      name:Department of Plant Pathology and Microbiology and Institute for Integrative Biology, University of California, Riverside, USA
      name:Institute of Plant Quarantine Research, Chinese Academy of Inspection and Quarantine, Beijing, China

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