2019
DOI: 10.1134/s0026893319010114
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A Pipeline for the Error-Free Identification of Somatic Alu Insertions in High-Throughput Sequencing Data

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Cited by 3 publications
(8 citation statements)
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“…We used a custom computational pipeline [27] to map all the sequenced insertions' flanks to the human reference genome. The method specificity that was calculated as the percentage of target RE flanks among all sequences was 0.87-0.96 for AluYa5, 0.86-0.92 for AluYb8, and 0.83-0.98 for L1HS.…”
Section: Validation Of Candidate Tumor-specific Insertionsmentioning
confidence: 99%
“…We used a custom computational pipeline [27] to map all the sequenced insertions' flanks to the human reference genome. The method specificity that was calculated as the percentage of target RE flanks among all sequences was 0.87-0.96 for AluYa5, 0.86-0.92 for AluYb8, and 0.83-0.98 for L1HS.…”
Section: Validation Of Candidate Tumor-specific Insertionsmentioning
confidence: 99%
“…After sequencing, we use a custom computational pipeline [ 24 ] to map all sequenced insertions flanks to the human genome. Coordinates of insertions in compared samples (e.g.…”
Section: Resultsmentioning
confidence: 99%
“…After sequencing (see Table 2 for sequencing read numbers) and data processing (as described previously in [ 24 ]) we searched for 5′ flanks of Alu insertions characteristic for genomes of individuals D2-D4 (from Table 1 ) in the corresponding datasets. As a result, we were able to identify 44 out of 44 insertions present in 1% (individual D2) of cells, 42–43 out of 45 insertions present in 0.3% (individual D3) of cells and 34–39 of 50 insertions present in 0.1% (individual D4) of cells (See Table 2 ).…”
Section: Resultsmentioning
confidence: 99%
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