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We are analyzing https://bmcbioinformatics.biomedcentral.com/articles/10.1186/1471-2105-13-154.

Title:
TAPDANCE: An automated tool to identify and annotate transposon insertion CISs and associations between CISs from next generation sequence data | BMC Bioinformatics | Full Text
Description:
Background Next generation sequencing approaches applied to the analyses of transposon insertion junction fragments generated in high throughput forward genetic screens has created the need for clear informatics and statistical approaches to deal with the massive amount of data currently being generated. Previous approaches utilized to 1) map junction fragments within the genome and 2) identify Common Insertion Sites (CISs) within the genome are not practical due to the volume of data generated by current sequencing technologies. Previous approaches applied to this problem also required significant manual annotation. Results We describe Transposon Annotation Poisson Distribution Association Network Connectivity Environment (TAPDANCE) software, which automates the identification of CISs within transposon junction fragment insertion data. Starting with barcoded sequence data, the software identifies and trims sequences and maps putative genomic sequence to a reference genome using the bowtie short read mapper. Poisson distribution statistics are then applied to assess and rank genomic regions showing significant enrichment for transposon insertion. Novel methods of counting insertions are used to ensure that the results presented have the expected characteristics of informative CISs. A persistent mySQL database is generated and utilized to keep track of sequences, mappings and common insertion sites. Additionally, associations between phenotypes and CISs are also identified using Fisherโ€™s exact test with multiple testing correction. In a case study using previously published data we show that the TAPDANCE software identifies CISs as previously described, prioritizes them based on p-value, allows holistic visualization of the data within genome browser software and identifies relationships present in the structure of the data. Conclusions The TAPDANCE process is fully automated, performs similarly to previous labor intensive approaches, provides consistent results at a wide range of sequence sampling depth, has the capability of handling extremely large datasets, enables meaningful comparison across datasets and enables large scale meta-analyses of junction fragment data. The TAPDANCE software will greatly enhance our ability to analyze these datasets in order to increase our understanding of the genetic basis of cancers.
Website Age:
25 years and 10 months (reg. 1999-08-06).

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Keywords {๐Ÿ”}

ciss, number, cis, insertions, file, transposon, insertion, sequence, sequences, total, window, genome, data, regions, mapping, mapped, figure, library, software, tapdance, pvalue, table, generated, pubmed, article, genomic, size, based, additional, analyses, datasets, cancer, region, identified, tumor, libraries, dataset, tumors, inserts, calculated, results, multiple, method, authors, methods, orientation, original, google, scholar, sequencing,

Topics {โœ’๏ธ}

author information authors springer nature transposon-genomic junction fragment forward genetic screen transposon-based genetic screen junction fragment data implementation availability requirements forward genetic screens discussion previously author correspondence conceptual discussion conclusions virus-based genetic screens transposon-genomic dna junctions authors scientific editing relevant information multi-mer ligation leading authorsโ€™ original file ligation adapter/linker sequence chip-seq randomly assigned high-throughput sequencing machine remaining genomic sequence information full size image content sb junction fragments genomic sequence adjacent captured genomic sequence flanking genomic sequence endogenous genomic sequence genomic sequence derived retroviral insertional mutagenesis transposon-based somatic mutagenesis de ridder bmc bioinformatics 13 window size thresholds original donor concatamer mobile genetic element privacy choices/manage cookies nature 2005 nature 486 low-level passenger insertions map junction fragments sleeping beauty-induced tumors maximum window size largest window size insertion-genomic junctions single genomic ciswindow

Schema {๐Ÿ—บ๏ธ}

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      headline:TAPDANCE: An automated tool to identify and annotate transposon insertion CISs and associations between CISs from next generation sequence data
      description:Next generation sequencing approaches applied to the analyses of transposon insertion junction fragments generated in high throughput forward genetic screens has created the need for clear informatics and statistical approaches to deal with the massive amount of data currently being generated. Previous approaches utilized to 1) map junction fragments within the genome and 2) identify Common Insertion Sites (CISs) within the genome are not practical due to the volume of data generated by current sequencing technologies. Previous approaches applied to this problem also required significant manual annotation. We describe Transposon Annotation Poisson Distribution Association Network Connectivity Environment (TAPDANCE) software, which automates the identification of CISs within transposon junction fragment insertion data. Starting with barcoded sequence data, the software identifies and trims sequences and maps putative genomic sequence to a reference genome using the bowtie short read mapper. Poisson distribution statistics are then applied to assess and rank genomic regions showing significant enrichment for transposon insertion. Novel methods of counting insertions are used to ensure that the results presented have the expected characteristics of informative CISs. A persistent mySQL database is generated and utilized to keep track of sequences, mappings and common insertion sites. Additionally, associations between phenotypes and CISs are also identified using Fisherโ€™s exact test with multiple testing correction. In a case study using previously published data we show that the TAPDANCE software identifies CISs as previously described, prioritizes them based on p-value, allows holistic visualization of the data within genome browser software and identifies relationships present in the structure of the data. The TAPDANCE process is fully automated, performs similarly to previous labor intensive approaches, provides consistent results at a wide range of sequence sampling depth, has the capability of handling extremely large datasets, enables meaningful comparison across datasets and enables large scale meta-analyses of junction fragment data. The TAPDANCE software will greatly enhance our ability to analyze these datasets in order to increase our understanding of the genetic basis of cancers.
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      dateModified:2012-06-29T00:00:00Z
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         Window Size
         Junction Fragment
         Forward Genetic Screen
         Genomic Window
         Flank Genomic Sequence
         Bioinformatics
         Microarrays
         Computational Biology/Bioinformatics
         Computer Appl. in Life Sciences
         Algorithms
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               type:PostalAddress
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               type:PostalAddress
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      name:Tim Starr
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            address:
               name:Obstetrics, Gynecology & Women's Health and Masonic Cancer Center, University of Minnesota, Minneapolis, USA
               type:PostalAddress
            type:Organization
      name:David A Largaespada
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            address:
               name:Department of Genetics, Cell Biology and Development and Pediatrics Masonic Cancer Center, University of Minnesota, Minneapolis, USA
               type:PostalAddress
            type:Organization
      name:Kevin A T Silverstein
      affiliation:
            name:University of Minnesota
            address:
               name:Biostatistics and Bioinformatics Masonic Cancer Center, University of Minnesota, Minneapolis, USA
               type:PostalAddress
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      name:Biostatistics and Bioinformatics Masonic Cancer Center, University of Minnesota, Minneapolis, USA
      name:Obstetrics, Gynecology & Women's Health and Masonic Cancer Center, University of Minnesota, Minneapolis, USA
      name:Department of Genetics, Cell Biology and Development and Pediatrics Masonic Cancer Center, University of Minnesota, Minneapolis, USA
      name:Biostatistics and Bioinformatics Masonic Cancer Center, University of Minnesota, Minneapolis, USA

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