Comments (1)
Hello @Karimi-81
Sorry for the late reply.
Regarding the scoring metric, there are some things to note:
- It was designed as a way of automatically scoring many comparisons (so to build further processing scripts on top of that in multiple comparisons)
- It is based on scoring continuous (adjacent) signals positively and discontinuos (gaps) signals negatively
- It does not take into account the actual signal (the alignments)
Now, regarding your experiments: without seeing the plots I am mostly guessing, but if there is a lot of fragmentation, and especially if the contigs/scaffolds are not in order, then the resulting signal in the plot will be extremely scattered. Given how the scoring metric is designed, each gap between fragments will count negatively, thus raising the score to 0.73.
On the other cases, 0.1 is usually is an indicator that most of the signal exists, even with large evolutionary events, see for instance:
In short, if the assembly level is below chromosome, the worse the score can be due to all the gaps and breaks between alignments (and this gets worse if with smaller and smaller contigs). I would recommend that you only use the scoring metric for its original purpose (such as automating scripts), or be careful about its interpretation!
Best regards,
Esteban
from chromeister.
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