simulate_sort is a program within the sortseq_tools package which simulates performing a Sort Seq experiment.
After you install `sortseq_tools`_, this program will be available to run at the command line.
usage: sortseq simulate_sort [-h] [-nm {LogNormal,Normal,None,Custom}]
[-npar NOISEPARAM] [-i I] [-n NBINS] [-o OUT]
| -nm=LogNormal, --noisemodel=LogNormal | |
Function module name that determines noisy expression from base expression. For example if your function is contained mynoisemodel.py enter mynoisemodel. The default noise model adds a set autoflourescence value and log-normal noise. The function name within the module should be gennoisyexp. Its first input argument must be the list of expression values, and the second should be a vector containing all other parameters as strings. If you would like no noise, enter None). Possible choices: LogNormal, Normal, None, Custom | |
| -npar=[.2,.2], --noiseparam=[.2,.2] | |
| Parameters for your noise model, as a list. The required parameters are LogNormal=[autoflouro,scale],Normal=[scale]. For custom models, enter a list of your parameters, with function name as the first entry. | |
| -i=False, --i=False | |
| Read input from file instead of stdin | |
| -n=4, --nbins=4 | |
| Number of bins to sort into. | |
| -o, --out | Undocumented |
The input table to this function must contain sequence, counts, and energy columns
Example Input Table:
seq ct val
AGGTA 5 -.4
AGTTA 1 -.2
...
Example Output Table:
seq ct val ct_1 ct_2 ct_3 ...
AGGTA 5 -.4 1 2 1
AGTTA 1 -.2 0 1 0
...
The output table will contain all the original columns, along with the sorted columns (ct_1, ct_2 ...)
An example command to execute this analysis:
sortseq simulate_sort -i my_library.txt -nm LogNormal -o my_sorted.txt