GenomeScope: Fast genome analysis from …
https://github.com/schatzlab/genomescope
Vurture, GW, Sedlazeck, FJ, Nattestad, M, Underwood, CJ, Fang, H, Gurtowski, J, Schatz, MC (2017) Bioinformatics doi: https://doi.org/10.1093/bioinformatics/btx153Getting StartedTutorialFrequently Asked Questions (FAQ)ResourcesReferences:Before running GenomeScope, you must first compute the histogram of k-mer frequencies. We … Before running GenomeScope, you must first compute the histogram of k-mer frequencies. We …Note you should adjust the memory (-s) and threads (-t) parameter according to your server. This example will use 10 threads and 1GB of RAM. The kmer length (-m) may need to be scaled if you have low coverage or a high error rate. We recommend using a kmer length of 21 (m=21) for mo… Then export the kmer count histogramAgain the thread count (-t) should be scaled according to your server. After you have the jellyfish histogram file, you can run GenomeScope within the online web tool, or at the command line.
Before running GenomeScope, you must first compute the histogram of k-mer frequencies. We …Note you should adjust the memory (-s) and threads (-t) parameter according to your server. This example will use 10 threads and 1GB of RAM. The kmer length (-m) may need to be scaled if you have low coverage or a high error rate. We recommend using a kmer length of 21 (m=21) for mo…
Then export the kmer count histogramAgain the thread count (-t) should be scaled according to your server. After you have the jellyfish histogram file, you can run GenomeScope within the online web tool, or at the command line.
DA: 77 PA: 87 MOZ Rank: 8
