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update readme
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LaraFuhrmann committed Aug 22, 2023
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# Quasispecies Reconstruction Benchmark
# Benchmarking module

Benchmark Quasispecies assembly methods both on the level of local as well as global haplotypes.
Benchmark Quasispecies assembly methods both on the level of SNVs as well as global haplotypes.

## Usage

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Analogously, PIP packages can be added by writing `# PIP: <package name>`.
Multiple packages can be added by repeating these lines.
A conda environment will then be dynamically generated (when running Snakemake with `--use-conda`).


## Configuring your benchmarking study

### Configuration file
`method_list` List of methods that should be executed. Methods should be defined as described above.
`replicate_count` Number of replicates per line in `params.csv` that should be created.
`haplotype_generation` Either `distance` or `mutation_rate`. In `distance` haplotypes are generated based on distance pattern, in the mode `mutation_rate` haplotypes are based on mutation, deletion and insertion rates indicated in the column `haplos` in `params.csv`.
`params_path` File path to parameter file `params.csv`.
`master_seq_path` Path to fasts file of master sequence that should be used for the generation of the haplotype population.

### Parameter file
This is a `csv`-file with the following columns:
`seq_tech` illumina, nanopore or pacbio
`seq_mode` shotgun, only for `illumina` we also have amplicon, in case of single_amplicon
`seq_mode_param` Parameters for amplicon mode. read_lenght:overlap.
`read_length` Read length
`genome_size` Genome size
`coverage` Coverage
`haplos`for distance mode: haplos = n_group1,n_group2,d_group12,d_group1,d_group2,freq_dist,freq_param
for mutation mode: haplos = mutation_rate,insertion_rate,deletion_rate,haplotype_pattern
parameters are seperated with "@"

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