Besides nucleotide diversity being important in cluster identification, obtaining a good nucleotide balance is important for successful basecalling to be performed.ĭe novo barcode design, i.e. Experiments show that reduced diversity in nucleotide composition results in data loss. For optimal detection, these two nucleotide groups should be in balance between all barcodes in each barcode position. For example, in Illumina sequencers, the nucleotides are detected using two lasers, red laser for A/C and green laser for G/T. Sequencing technology may give further restrictions for barcodes being optimal. More generally, in order to tolerate m mismatches, the distance between all barcode pairs should be at least 2 m+1. For example, in order to tolerate a single nucleotide mismatch in barcode detection, different barcode sequences should be at least three nucleotide mismatches apart from each other. Redundancy in the barcode sequence provides the possibility for error correction. In order to work properly, barcode sequences should be sufficiently different from each other. The two processes, mixing the samples and then separating them after sequencing are also called multiplexing and demultiplexing, respectively. These barcode sequences are attached to the fragments during the library preparation. A standard solution is to use a short barcode sequence for labeling different samples. This introduces the problem how to separate different samples after sequencing. Therefore, several sequencing libraries are pooled together and sequenced in parallel using the same lane in the sequencing apparatus. If application requires only few tens of millions of reads per sample, it would be waste of resources to allocate an entire lane for a single sample. For example, at the moment, a single lane of Illumina HiSeqX produces hundreds of millions reads per run and the new NovaSeq can produce billions of sequences per run. It is a common practice to pool several samples together in order to maximize the usage of the capacity of high-throughput sequencing platforms. The tool is easy to access via web browser. Our method allows the user to select a given number of barcodes among the larger existing barcode set so that both sequencing errors are tolerated and the nucleotide balance is optimized. Increasing capacity of sequencing platforms raises the challenge of mixing barcodes. The method is implemented in C programming language and web interface is available at. Based on the desired number of barcodes to be selected and the set of candidate sequences given by user, the necessary constraints are automatically generated and the optimal solution can be found. We define the cost function and a set of constraints and use integer programming to solve the resulting combinatorial problem. In our approach the selection process is formulated as a minimization problem. whether two or more libraries with existing barcodes can be combined in a single sequencing pool, and 3) augmenting an existing set of barcodes. We have developed a tool which can be used for three different tasks: 1) selecting an optimal barcode set from a larger set of candidates, 2) checking the compatibility of user-defined set of barcodes, e.g. There are plenty of tools available for de novo barcode design, but they are not suitable for subset selection. The number of samples to be mixed in each sequencing run may vary and this introduces a problem how to select the best subset of available barcodes at sequencing core facility for each sequencing run. An additional constraint due to both nucleotide usage and basecalling accuracy is that the proportion of different nucleotides should be in balance in each barcode position. In order to tolerate sequencing errors, barcodes should be sufficiently apart from each other in sequence space. After sequencing, the samples are binned by identifying the barcode sequence within each sequence read. Different samples are labeled by attaching a short sample specific nucleotide sequence, barcode, to each DNA molecule prior pooling them into a mix containing a number of libraries to be sequenced simultaneously. Current high-throughput sequencing platforms provide capacity to sequence multiple samples in parallel.
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