Journal: eLife
Article Title: Barcode-free multiplex plasmid sequencing using Bayesian analysis and nanopore sequencing
doi: 10.7554/eLife.88794
Figure Lengend Snippet: ( a ) Density plot of the rate of reads with correct base calling. The rate was calculated at each position of plasmids and displayed using representative nanopore sequencing results. ( b ) Averaged quality score distribution of reads with correct rate of less than 0.7 (upper panel) and more than 0.9 (bottom panel). The corresponding regions are displayed with dashed red frames in ( a ). Of note, ‘omitted’ represents reads that did not cover the focused position. ( c ) Probability logo plot. Statistical significance (−log 10 [p-value]) was calculated for a 5-mer around the positions that showed correct rate lower than 0.7 in ( a ) using those that showed more than 0.9 as a background. Enriched residues are stacked on the top, whereas depleted residues are stacked on the bottom. ( d ) Estimated probability of incorrect classification. Based on the match/mismatch/deletion ratio of reads obtained in the ‘worst-case scenario’, i.e., top panel in ( b ), the probability of incorrect classification of a read was calculated assuming that two plasmids that differ by the indicated base(s) were mixed. ( e ) Estimated probability of correct/incorrect consensus base calling. Based on the quality score distribution obtained in the ‘worst-case scenario’, i.e., top panel in ( b ), the indicated number of reads were generated in silico, and the consensus base calling was calculated using Simple Algorithm for Very Efficient Multiplexing of Oxford Nanopore Experiments for You (SAVEMONEY). The simulation was performed 10,000 times for each condition to calculate the probability of correct/incorrect consensus base calling. Figure 6—source code 1. Source code used to make . Figure 6—source code 2. Source code used to make . Figure 6—source data 1. Csv file containing raw data used to make . Figure 6—source data 2. Csv file containing raw data used to make . Figure 6—source data 3. Text file containing raw data used to make . Figure 6—source data 4. Csv file containing raw data used to make .
Article Snippet: Here, we have developed a barcode-free, easy-to-use computational approach termed Simple Algorithm for Very Efficient Multiplexing of Oxford Nanopore Experiments for You (SAVEMONEY) that guides users to pool samples for nanopore sequencing and effectively reduces sequencing costs to as low as $2.50 (USD) per plasmid, which is about twice less expensive than one reaction of Sanger sequencing.
Techniques: Nanopore Sequencing, Generated, In Silico, Multiplexing
SAS institute is a verified supplier 
![( a ) Density plot of the rate of reads with correct base calling. The rate was calculated at each position of plasmids and displayed using representative nanopore sequencing results. ( b ) Averaged quality score distribution of reads with correct rate of less than 0.7 (upper panel) and more than 0.9 (bottom panel). The corresponding regions are displayed with dashed red frames in ( a ). Of note, ‘omitted’ represents reads that did not cover the focused position. ( c ) Probability logo plot. Statistical significance (−log 10 [p-value]) was calculated for a 5-mer around the positions that showed correct rate lower than 0.7 in ( a ) using those that showed more than 0.9 as a background. Enriched residues are stacked on the top, whereas depleted residues are stacked on the bottom. ( d ) Estimated probability of incorrect classification. Based on the match/mismatch/deletion ratio of reads obtained in the ‘worst-case scenario’, i.e., top panel in ( b ), the probability of incorrect classification of a read was calculated assuming that two plasmids that differ by the indicated base(s) were mixed. ( e ) Estimated probability of correct/incorrect consensus base calling. Based on the quality score distribution obtained in the ‘worst-case scenario’, i.e., top panel in ( b ), the indicated number of reads were generated in silico, and the consensus base calling was calculated using Simple Algorithm for Very Efficient Multiplexing of Oxford Nanopore Experiments for You <t>(SAVEMONEY).</t> The simulation was performed 10,000 times for each condition to calculate the probability of correct/incorrect consensus base calling. Figure 6—source code 1. Source code used to make . Figure 6—source code 2. Source code used to make . Figure 6—source data 1. Csv file containing raw data used to make . Figure 6—source data 2. Csv file containing raw data used to make . Figure 6—source data 3. Text file containing raw data used to make . Figure 6—source data 4. Csv file containing raw data used to make .](https://pub-med-central-images-cdn.bioz.com/pub_med_central_ids_ending_with_9211/pmc12029211/pmc12029211__elife-88794-fig6.jpg)
