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To assess differences in the potential metabolism of organisms found within sites exhibiting disparate geochemistry, we searched the five metagenomic assemblies using query sequences (Table S3) of proteins associated with specific autotrophic (CO2 fixation) pathways and electron transfer processes involving C, Fe, S, As, N, H2 or O2 (Table 2).
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Omega is a metagenomic assembler using overlap graph approach.
The above-mentioned studies of metagenomic assembly all used bacterial communities and mainly focused on assessing functional and taxonomic annotations.
We performed and assembly using metagenomic data obtained from the stool sample.
Both assemblies used similar Sulston scores.
Due to the high computational requirements for the assembly of our metagenomic datasets, we used ABYSS [ 6] assembler (version - 1.0.8) which can perform parallel assembly using a cluster of commodity computers.
The resulting long reads were used to generate metagenomic assemblies (Table 2, see 'Materials and methods') which served as input to PhyloPhlAn (Segata et al., 2013).
We present Athena, a de novo assembler that uses read clouds to improve metagenomic assemblies.
Another strategy, which is more common and often used before metagenomic assembly, is to normalize the sequencing reads using bioinformatic methods (Rodrigue et al., 2009) such as screening and trimming the reads according to their k-mer depth.
We have also assessed the degree of chimericity of the assembled contigs using an entropy/impurity metric and compared the metagenomic assemblies to assemblies of isolated individual source genomes.
We have evaluated metagenomic assemblies based on the accuracy of the generated contigs using alignment-based similarity to the source genomes, contig length statistics, and the proportions of the source genomes recovered by the contigs.
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