![]() As another example, Stampy performs read alignment using a read search method, with a hash table constructed by hashing a k-mer-sized sequence from a reference sequence. However, rapid sorting is difficult to achieve, because the hash table for each query sequence has to be newly constructed by read-hashing based on the query sequence rather than a reference sequence, and the reference sequence has to be scanned multiple times. For instance, MAQ performs read alignment by constructing short reads of the query sequence as a hash table and searching for reference sequences. ![]() While these tools generate hash tables and functions for short-read sorting, their applicability for read alignment has also been investigated. cPlot identifies the location and order of the sequencing reads by comparing the sequence to a genetically close reference sequence in a way that is effective for visualizing the assembly of short reads generated by NGS and rapid gene map construction.Įxamples of the currently used alignment programs include MAQ, Stampy, and ntHash. This application provides a web-based interface for the user for facile implementation, without the need for a dedicated computing environment. cPlot compares sequence similarity of reads by performing multiple read alignments, with FASTA format files as the input. We, here, devised cPlot software for read alignment of nucleotide sequences, with automated read alignment and position analysis, which allows visual assessment of the analysis results by the user. However, read alignment from vast amounts of genomic data from various organisms is challenging in that it involves repeated automatic and manual analysis steps. In addition, it is essential to analyze the results of read alignments for a biologically meaningful inference. ![]() Reconstruction of short DNA sequence reads generated by next-generation sequencing requires a read alignment method that reconstructs a reference genome. Advances in the next-generation sequencing technology have led to a dramatic decrease in read-generation cost and an increase in read output. ![]()
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