Skip to main content


Springer Nature is making SARS-CoV-2 and COVID-19 research free. View research | View latest news | Sign up for updates

Fig. 4 | BMC Bioinformatics

Fig. 4

From: Improving contig binning of metagenomic data using \( {d}_2^S \) oligonucleotide frequency dissimilarity

Fig. 4

The effect of the order of Markov chain on the binning of contigs with different binning algorithms (MaxBin, MaxCluster, MetaWatt, SCIMM and MyCC) further modified by \( {d}_2^S\mathrm{Bin} \) for 6-tuples on dataset 10genome 80×. a-e are the Recall, Precision and ARI of 0–2 order of Markov chain to calculate \( {d}_2^S\mathrm{Bin} \) on the five contig-binning tools. From the figures, it can be clearly seen that \( {d}_2^S\mathrm{Bin} \) calculated on 0-order Markov chain achieves the best performance in all cases

Back to article page