Sentence examples for removed sequences for from inspiring English sources

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In some regions of the 16S data, the ability to align the polypterid taxa was improved if we removed sequences for the outgroup taxa (and their corresponding data replaced with "?" in these regions).

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Subsequently, these sequences were aligned using a global alignment algorithm to remove sequences for which the best blast hit represented only local homology.

After removing sequences for partial domains, 25 genes that encoded full KS domains in S. minutum were selected for sequence characterization (Table  1; see Additional file 1: Table S1) and molecular phylogenetic analysis.

Hence, we submitted each of our single-gene alignments to ML reconstructions with bootstrap replications and systematically removed sequences that displayed ambiguous phylogenetic positions for both paralogy and gene transfers.

Either using ILD to test incongruence between each gene against the all remaining (in this case 10) genes in order to remove sequences responsible for significant incongruence, or using just a simultaneous analysis without removals, gave robust phylogenies with slight topological differences.

First, we removed sequencing errors using small k-mers for graph building, and then we rebuilt the graph using larger k-mers iteratively by mapping the reads back to the previous DBG to resolve longer repeats.

It should be noted that these estimates are obtained after removing sequences that showed evidence for rare recombination events between the two chromosomal backgrounds (gene conversion tracts).

For example, after removing sequences with identities higher than 95%%, only 75 out of the over 5,000 total genomes are left in PASC for the family Hepadnaviridae (as of April, 2014).

As an additional pre-processing step, Bowtie 2 [ 29] can be used to identify and remove sequence reads matching (for example, the human genome), which is useful, for example, when working with metagenomic data from human microbiomes.

We avoided over-optimistic performance estimates by removing sequence similarity between proteins used for method development (training/cross-training) and testing.

Clustering is regularly used for detecting and removing sequencing artifacts from 454 data [ 13, 14], grouping rRNA data into operational taxonomic units (OTUs) [ 15, 16], and grouping proteins into families [ 17, 18].

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