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Table 1 Coverage biases in metagenome assemblies

From: A scalable assembly-free variable selection algorithm for biomarker discovery from metagenomes

Abundance class (Bin #) Bin abundance level % Binned reads in assembly Estimated number of genomes in bin
Bin I 320 2.8 % > = 3
Bin II 180 2.9 % > = 1
Bin III 90 12.6 % > = 2
Bin IV 30 54.0 % > = 6
Bin V 9 0.5 % > = 3
  1. Unassembled (raw) reads derived from a xenobiotic degrading bacterial consortium (Chaussonerie et al. 2016 under review) were segregated by the AB-Cl module (k-mer size = 25) into 5 abundance classes (bins). Mapping of reads from individual bins on the metagenome assembly based on all the raw reads reveals a significant under-representation of abundance classes I, II, III and V