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Table 2 Comparison of workflows for the assembly and annotation of eDNA insert data using Lam et al. [16] pooled inserts

From: A-GAME: improving the assembly of pooled functional metagenomics sequence data

  Insert assignment based on end-tags Completeness Computational requirements
  Completea 2 of 2 endsb 1 of 1 endsc Partiald % assemblede % of reference proteinsf Assembly N50 CPU time (h) RAM peak (Gb)
original assembly 40 6 10 11 100.00 100.00 36,113 NA NA
SPAdes (F1) 34 13 9 11 88.16 86.35 34,329 2.03 5.3
Velvet (F2) 18 27 10 12 66.58 64.79 32,942 1.67 6.61
MEGAHIT (F3) 30 19 8 10 95.14 92.13 34,446 1.21 3.22
MetaVelvet (F4) 19 26 9 13 74.64 73.38 33,150 1.75 7.01
meta-SPAdes (F5) 34 13 9 11 88.16 86.35 34,329 2.03 5.3
MOCAT2 19 27 8 13 67.62 65.92 25,246 1.91 4.51
Parallel META2 12 34 6 15 40.48 37.87 26,408 2.36 3.11
Original from LAM et al 19 28 7 13 72.47 69.97 33,347 NA NA
  1. aInsert assembled into a single contig matching both end tags
  2. bInserts assembled into multiple contigs, both end tags are assigned
  3. cInserts for which only a single end tag is available and gets assigned
  4. dInserts for which both ends are available but only one is assigned
  5. ePercentage of reference assembly represented in the pooled assembly
  6. fPercentage of proteins from the reference assembly recovered in the pooled assembly
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