Seqreppy is a Python library for numerical representations of genomic sequences.
Clone this repository or download the code (and unzip the file). Go inside the seqreppy directory and run the shell script bellow:
sudo ./install-seqreppy.sh
Obs: make sure that script file is executable in your system (use chmod command). I'm assuming that you are on a Linux Distribution. In future i'll make available a script for Windows.
I wrote bellow some code examplifying the functionalities of Seqreppy
from seqreppy.sp import sp # Core Functionalities
## -- -- -- -- -- -- -- -- Seqreppy Core Functionalities -- -- -- -- -- ##
## -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- ##
## Seqreppy uses SeqrepC module for do the following core operations
## SeqrepC is writed in C language
##-- sp.encode_from_file(<methods signatures>, <directory of fasta file>)
encodings = sp.encode_from_file(("cgr", "icgr"), "/home/ednilson/file.fasta")
##-- Using just one representation method
# encodings = sp.encode_from_file("cgr", "/home/ednilson/file.fasta")
##-- Using 2 or more sequences on memory.
# encodings = sp.encode_from_strings(("cgr", "icgr"), ("ATCCCGA", "CTGGGA"))
##-- Using just 1 sequence on memory.
# encodings = sp.encode_from_strings(("cgr", "icgr"), ("ATCCGAATCGA",))
##--! IMPORTANT NOTE 1 !--##
##-- Encodings are a dictionary. Each value of it is an iterable
##-- representing a pool of sequences encoded by the respectivelly
##-- method signature, corresponding to the keys of dictionary.
##-- If your file has 3 sequeces, encodings["cgr"][1] get the second
##-- sequece. If your file has just one sequence, it will be the first:
##-- encodings["cgr"][0], following the order of appereance on fasta file.
##-- I have 2 encoding methods, so, 2 destinies
sp.save_results(encodings, "/dir/cgr.txt", "/dir/icgr.txt")
##-- In case just one encoding method, one destiny
# sp.save_results(encodings, "/home/ednilson/la")
# sp.get_results receives a dict, in with the keys are the method signatures
# and the values are the location (directory)
z = sp.get_results({"cgr": "/dir/cgr.txt", "icgr": "/dir/icgr.txt"})
##-- In case just one encoding method, one location
# z = sp.get_results({"atomic": "/home/ednilson/la"})
## -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- ##
## -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- ##
Currently, Seqreppy has 16 numerical representation methods identified by the signatures below:
- atomic
- cgr
- imaginary
- dna_walk
- liao
- eiip
- binary2b
- binary4b
- integer
- icgr
- molecular_mass
- paired_numeric
- real
- tetrahedron
- voss
- zcurve
if you wanna numerical representations details, you can read a short summary here
If you need some graphical visualisation, seqreppy has optional packages to do it for you. This optional packages has NumPy and Matplotlib as dependencies. So, you need to install it:
python -m pip install -U matplotlib
pip install numpy
I wrote bellow some methods you can use additionally to the core functionalities written above.
from seqreppy.sp import sp # Core Functionalities
from seqreppy.gsp import gsp # !-- Optional --! Genomic Signal Processing
from seqreppy.view import view # !-- Optional --! -> Graphical visualizations
## -- -- -- -- -- -- -- -- -- OPTIONAL MODULES -- -- -- -- -- -- -- -- ##
## -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- ##
## just in case if you want to analyse graphically or
## apply some Genomic Signal Processing analysis
##-- lets get the results saved before
encodings = sp.get_results({"cgr": "/dir/cgr.txt", "icgr": "/dir/icgr.txt"})
##-- view.visualize(<method signature>, <sequence>)
view.visualize("cgr", encodings["cgr"][0])
view.visualize("icgr", encodings["icgr"][0])
##-- view.save_figure(<method signature>, <sequence>, <kargs>)
view.save_figure("cgr", encodings["cgr"][0], dpi=600, fname="file_name.png")
##-- kargs are not a rule. You can leave it with None.
view.save_figure("cgr", encodings["cgr"][0])
##-- lets get some encodings for apply gsp analysis
z = sp.encode_from_file("atomic", "/home/ednilson/file.fasta")
##-- gsp.apply_gsp(<function>, <encodings>)
z = gsp.apply_gsp(gsp.power_spectrum, z)
##-- view.visualize_power_spectrum(<method signature>, <sequence>, <kargs>)
view.visualize_power_spectrum("atomic", z["atomic"][0])
##-- you can specify a range of the power spectrum
view.visualize_power_spectrum("atomic", z["atomic"][0], start=1, end=100)
## -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- -- ##
If you have some new method developed by you or that is not present on Seqreppy, please, contribute! If you see some code that can be writed in a more efficient way, great! Let me know! If you saw interpretation erros in methods implementation, please, tell me, and i will make the corrections as soon as possible!
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