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. 3 | BMC Bioinformatics

Fig. 3

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

Fig. 3

The effect of tuple length on the binning of contigs with different binning algorithms (MaxBin, MaxCluster, MetaWatt, SCIMM and MyCC) further modified by \( {d}_2^S\mathrm{Bin} \) under the i.i.d. background model for dataset 100genome simHC+. a-e are the Recall, Precision and ARI of 4–6 tuples \( {d}_2^S\mathrm{Bin} \) on the five contig-binning tools. From the figures, it can be clearly seen that 6-tuple \( {d}_2^S\mathrm{Bin} \) achieves the best performance in almost all cases

Back to article page