Kmergenie
Application data |
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Created by | R. Chikhi, P. Medvedev |
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Biological application domain(s) | Sequence assembly |
Principal bioinformatics method(s) | Sequence assembly |
Technology | Illumina |
Created at | Penn State University |
Maintained? | Yes |
Input format(s) | Fasta/Fastq |
Output format(s) | HTML report |
Programming language(s) | C++, Python, R |
Summary: KmerGenie estimates the best k-mer length for genome de novo assembly. Given a set of reads, KmerGenie first computes the k-mer abundance histogram for many values of k. Then, for each value of k, it predicts the number of distinct genomic k-mers in the dataset, and returns the k-mer length which maximizes this number. Experiments show that KmerGenie's choices lead to assemblies that are close to the best possible over all k-mer lengths.
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