We are analyzing https://link.springer.com/article/10.1186/s12859-015-0454-y.

Title:
TagDust2: a generic method to extract reads from sequencing data | BMC Bioinformatics
Description:
Background Arguably the most basic step in the analysis of next generation sequencing data (NGS) involves the extraction of mappable reads from the raw reads produced by sequencing instruments. The presence of barcodes, adaptors and artifacts subject to sequencing errors makes this step non-trivial. Results Here I present TagDust2, a generic approach utilizing a library of hidden Markov models (HMM) to accurately extract reads from a wide array of possible read architectures. TagDust2 extracts more reads of higher quality compared to other approaches. Processing of multiplexed single, paired end and libraries containing unique molecular identifiers is fully supported. Two additional post processing steps are included to exclude known contaminants and filter out low complexity sequences. Finally, TagDust2 can automatically detect the library type of sequenced data from a predefined selection. Conclusion Taken together TagDust2 is a feature rich, flexible and adaptive solution to go from raw to mappable NGS reads in a single step. The ability to recognize and record the contents of raw reads will help to automate and demystify the initial, and often poorly documented, steps in NGS data analysis pipelines. TagDust2 is freely available at: http://tagdust.sourceforge.net .
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28 years and 1 months (reg. 1997-05-29).

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Keywords {🔍}

tagdust, reads, sequences, sequencing, read, article, barcodes, sequence, data, google, scholar, raw, hmm, barcode, mapping, pubmed, additional, cas, processing, architectures, error, analysis, figure, number, full, demultiplexing, model, architecture, probability, algorithm, information, lassmann, ngs, compared, libraries, length, genome, random, nucleotide, size, sample, panels, extract, access, mappable, presence, library, quality, automatically, pcr,

Topics {✒️}

single-cell transcriptional landscape bar-coded multiplexed sequencing highly multiplex rna-seq open access license article download pdf related subjects full size image fast bit-vector algorithm high-throughput sequencing reads generation sequencing technologies generation sequencing data full profile hmms timo lassmann privacy choices/manage cookies general area including multiplexed paired-end samples unix/linuxprogramming language article lassmann tagdustproject home page sequencing errors makes full access optimal accuracy decoding low complexity sequences short command line european economic area dna sequencing metagenomics author information authors sequencing error rate de-multiplexing functionality de-multiplexing separately low complexity reads sequencing errors occur unique molecular identifiers sequencing error rates additional background hmm hidden markov models guaranteeing good accuracy generated large datasets low-complexity filter thresholds greatly simplifies riken yokohama institute additional reads extracted thread level parallelism literate programming paradigm basic de-multlexing counting absolute numbers generation sequencing protocol specific scripts higher quality compared main content log

Schema {🗺️}

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      headline:TagDust2: a generic method to extract reads from sequencing data
      description:Arguably the most basic step in the analysis of next generation sequencing data (NGS) involves the extraction of mappable reads from the raw reads produced by sequencing instruments. The presence of barcodes, adaptors and artifacts subject to sequencing errors makes this step non-trivial. Here I present TagDust2, a generic approach utilizing a library of hidden Markov models (HMM) to accurately extract reads from a wide array of possible read architectures. TagDust2 extracts more reads of higher quality compared to other approaches. Processing of multiplexed single, paired end and libraries containing unique molecular identifiers is fully supported. Two additional post processing steps are included to exclude known contaminants and filter out low complexity sequences. Finally, TagDust2 can automatically detect the library type of sequenced data from a predefined selection. Taken together TagDust2 is a feature rich, flexible and adaptive solution to go from raw to mappable NGS reads in a single step. The ability to recognize and record the contents of raw reads will help to automate and demystify the initial, and often poorly documented, steps in NGS data analysis pipelines. TagDust2 is freely available at: http://tagdust.sourceforge.net .
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         Bioinformatics
         Microarrays
         Computational Biology/Bioinformatics
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         Algorithms
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