Wrapper for the simulation of reads

This generates a datavolume of 10000 base pairs in total.

python "readsimulationwrapper.py" 10000 \
-i abundance.tsv \
-l genome_locations.tsv \
-o dir_output/ \
-art art_illumina \
-epd dir_profile/ \
-ep "hi150" \
-sd 27 \
-m 270

Use "-seed myseed" for consitent results. Or "-p 10" to use 10 cores at the same time.

Tab separated.
Abundance reflects genome abundance, not data abundance!

• column 1: genome id
• column 2: relative abundance

Tab separated.

• column 1: genome id
• column 2: file path to fasta file

Search in "readsimulationwrapper.py" for the class definition of "ReadSimulationArt" and find the lines:

_art_error_profiles = {
	"mi": "EmpMiSeq250R",
	"hi": "EmpHiSeq2kR",
	"hi150": "HiSeq2500L150R"}

If someone made new profile files like "HiSeq_5000_L250R_1.txt" and "HiSeq_5000_L250R_2.txt", one only needs to add them like this:

_art_error_profiles = {
	"mi": "EmpMiSeq250R",
	"hi": "EmpHiSeq2kR",
	"hi150": "HiSeq2500L150R",
	"hi250": "HiSeq_5000_L250R_"}