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Matches in UGent Biblio for { ?s ?p Next-generation amplicon resequencing allows rapid identification of novel or known SNPs and mutations. However, sample preparation remains a largely manual and sometimes tedious task, especially when large pools of samples need to be analyzed. Multidimensional pooling is a technique where a sample is duplicated in a combination of pools in such a way that every sample is included in a unique combination of pools. This pooling technique allows a drastic reduction of sample pools (from x^y samples to x*y pools, for example 125 samples to 15 pools) but complicates downstream data analysis. We developed a simulation and analysis pipeline - called SNP-Cub^3 - for 3D pooled illumina resequencing that allows optimization and scaling of the multidimensional pools, optimization of the sequencing setup and analysis of the sequencing data. A drawback of this pooling approach is that variant frequencies in a single pool are very low. For example: in a multidimensional pool where 25 samples are included into 1 pool, a homozygous variant or SNP in a single sample will appear as a 4% variant in the total pool. Although this frequency is higher than the sequencing error rate or PCR error rate, stochastic effects can make it difficult to classify this as a variant or a sequencing/PCR error. The pipeline is able to overcome this limitation by comparing variant frequencies in several pools wherein a single sample is included. A real sample variant (unique to that sample) in a 3D-pooled setup should appear in 3 pools with the same frequency. SNP-cub^3 is able to assign a p-value, which is the probability that a real variant would be randomly sampled at the observed frequencies in the different pools, to an observed variant. The simulation module of the pipeline allows a user to experimentally validate the limits of this approach by altering the number of samples and pools in combination with a predefined PCR and sequencing error rate which is used to generate simulated reads.. }

• aggregation abstract "Next-generation amplicon resequencing allows rapid identification of novel or known SNPs and mutations. However, sample preparation remains a largely manual and sometimes tedious task, especially when large pools of samples need to be analyzed. Multidimensional pooling is a technique where a sample is duplicated in a combination of pools in such a way that every sample is included in a unique combination of pools. This pooling technique allows a drastic reduction of sample pools (from x^y samples to x*y pools, for example 125 samples to 15 pools) but complicates downstream data analysis. We developed a simulation and analysis pipeline - called SNP-Cub^3 - for 3D pooled illumina resequencing that allows optimization and scaling of the multidimensional pools, optimization of the sequencing setup and analysis of the sequencing data. A drawback of this pooling approach is that variant frequencies in a single pool are very low. For example: in a multidimensional pool where 25 samples are included into 1 pool, a homozygous variant or SNP in a single sample will appear as a 4% variant in the total pool. Although this frequency is higher than the sequencing error rate or PCR error rate, stochastic effects can make it difficult to classify this as a variant or a sequencing/PCR error. The pipeline is able to overcome this limitation by comparing variant frequencies in several pools wherein a single sample is included. A real sample variant (unique to that sample) in a 3D-pooled setup should appear in 3 pools with the same frequency. SNP-cub^3 is able to assign a p-value, which is the probability that a real variant would be randomly sampled at the observed frequencies in the different pools, to an observed variant. The simulation module of the pipeline allows a user to experimentally validate the limits of this approach by altering the number of samples and pools in combination with a predefined PCR and sequencing error rate which is used to generate simulated reads.".