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Table 2 Evaluation parameters used in TransFlow, described by their name, the software that calculates the parameter (FLN: Full-LengtherNext), a brief description of its meaning and the expected trend for such a parameter

From: TransFlow: a modular framework for assembling and assessing accurate de novo transcriptomes in non-model organisms

Parameter name Software Description Trenda
AllTransSize FLN The sum of every transcript length in nucleotides ↓
N50 FLN The shortest contig(or scaffold) length (in nucleotides) in the set needed to cover 50% of AllTransSize ↑
N90 FLN The shortest contig (or scaffold) length (in nucleotides) in the set needed to cover 90% of AllTransSize ↑
Contigs FLN Number of contigs mapping at least one pair of reads ↓
Contigs500 FLN Same as previous, but taking into account only contigs > 500 nt ↑
MeanContigLen FLN Mean sequence length (in nucleotides) across all useful contigs or scaffolds ↑
Ns FLN Number of Ns (indeterminations) in the contigs or scaffolds ↓
MeanGapLen FLN Mean indetermination length in nucleotides, where 1 indicates that gaps are randomly distributed, and greater values indicate real gaps ↓
DiffProts FLN Number of unique, different proteins ↑
DiffComplProts FLN Same as previous, but onlyconsidering those proteins that seem to be complete ↑
MissAssembl FLN Percentage of contigs where the annotating protein finds similarity in both plus and minus strands ↓
MeanContigCov FLN Fraction of the contig lengths (expressed as percentage) covered by mapped reads. This fraction is calculated per contig an then averaged for the full assembly ↑
ComplOrtho BUSCO Percentage of OrthoDB orthologues from a lineage fully identified in one single contig ↑
FragOrtho BUSCO Percentage of OrthoDB orthologues from a lineage that are fragmented across several contigs ↑
DuplOrtho BUSCO Percentage of OrthoDB orthologues from a lineage that are repeated in several contigs ↓
  1. All parameters are calculated for every assembly
  2. a ↑ indicates that the higher the value, the better the transcriptome; ↓ indicates that this value should be maintained in good transcriptomes as low as possible
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BMC Bioinformatics

ISSN: 1471-2105

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