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The break points detected using REDHORSE as well as the other existing RD algorithms are visually depicted using these plots.
Since the ME49 genome is haploid, we extracted the alleles with frequency greater than or equal to 80% and having a minimum coverage of 5 using REDHORSE [ 33].
This resulted in a final list of 499,470 loci that were used to detect conventional crossovers as well as double crossovers using REDHORSE.
We identified a total of 532,949 SNPs in VAND and 1,821 SNPs in ME49 to compare raw reads to the reference ME49 genome in ToxoDB using REDHORSE [ 33].
Based on these loci as markers and using allele information generated using REDHORSE, it builds a "merged allele file" that contains physical marker positions as well as nucleotide composition of all the samples at those markers.
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We demonstrated the utility of REDHORSE using simulated data and real Next-generation sequencing data.
REDHORSE uses alignments of NGS reads to the genome of interest as input.
The utility of REDHORSE was demonstrated using both the simulated data and NGS data.
The utility of REDHORSE is demonstrated using simulated datasets as well as NGS data.
The RD algorithm in REDHORSE extracts recombinations from NGS datasets using not only the contigs but also using genomic positions of the markers that were used to build the contigs.
REDHORSE implements a custom built algorithm to identify SNVs using the allele file and the reference fasta file.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com