Inflation expansion

We can use UMIche to draw deduplication performance of Markov clustering versus its two important parameters, inflation and expansion.

Python 

 1
 2
 3
 4
 5
 6
 7
 8
 9
10
11
12
13
14
15
16
import umiche as uc

df = uc.plot.inflat_exp(
    scenarios={
        'pcr_nums': 'PCR cycle',
        'pcr_errs': 'PCR error',
        'seq_errs': 'Sequencing error',
        'ampl_rates': 'Amplification rate',
        'umi_lens': 'UMI length',
        'seq_deps': 'Sequencing depth',
    },
    methods={
        'mcl': 'MCL',
    },
    param_fpn=to('data/params.yml'),
).draw()

Image title
Fig 1. Fold change between estimated and actual deduplicated counts with respect to the inflation (a) and expansion (b) parameters of the MCL algorithm.