Your English writing platform
Discover LudwigSuggestions(1)
Exact(2)
Sequences greater than 97% identical, determined by pairwise alignment within the dataset, were also removed.
In order to avoid statistical bias, the functional classes represented by less than a hundred sequences, namely [M], [N] and [Y], accounting overall for less than one percent of the all dataset, were also removed.
Similar(58)
Those datasets which had been contributed by the same research group as the three source datasets, GSE3526 for instance, were also removed from our test set.
Adaptor sequences were also removed from the dataset.
Lines that were genotyped at less than 20%% loci were also removed from the dataset.
Sequences which did not align correctly were also removed from the dataset.
345 SNPs with allele frequencies of less than 10percentt (in fewer than 4 genomes) were also removed from the dataset, leaving 122 candidate SNPs.
In addition, sequences that did not have the exact primer sequence, sequences that contained an ambiguous base (N), sequences having a homopolymer stretch longer than 8 bases, and sequences shorter than 80 bp were also removed from the datasets using trim.seqs command in MOTHUR.
Moreover, the sequencing reads containing primer mismatches, uncorrectable barcodes, ambiguous bases, or homopolymer runs in excess of 8 bp were also removed from both datasets.
Redundant contigs were also removed from the raw contig set via homology searches with duplicative or non-duplicative protein datasets of various plants instead of the A. thaliana gene dataset.
Duplicate publications were also removed.
Write better and faster with AI suggestions while staying true to your unique style.
Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com