BE_Endo

title: Deep learning models incorporating endogenous factors beyond DNA sequences improve the prediction accuracy of base editing outcomes

##download git clone https://github.com/zhaodalv/BE_Endo.git (No further action is required!!) Or download zip file at https://github.com/zhaodalv/BE_Endo Once downlaod the zip file the "-master" suffix need to removed by this command: "mv BE_Endo-master BE_Endo", which is a necessary step to run the progam!!!

####set up running envirnoment within conda version 4.14.0

1. create running ENV (BE_Endo) conda create -n BE_Endo python=3.9.4
2. activating ENV (BE_Endo) conda activate BE_Endo 3)install package dependency conda install -c conda-forge joblib=0.17.0 conda install -c conda-forge numpy=1.20.2 conda install -c conda-forge pandas=1.2.4 conda install -c anaconda scipy=1.6.2 conda install -c anaconda seaborn=0.11.2 conda install -c anaconda statsmodels=0.12.2 conda install tensorflow=2.4.1 // conda install -c conda-forge tensorflow=2.4.1 conda install -c bioconda bedtools=2.29.1 conda install -c anaconda scikit-learn=0.24.2
3. add package path to environment export PYTHONPATH=$PYTHONPATH:{PATH of BE_Endo Package} example: export PYTHONPATH=$PYTHONPATH:~/BE_Endo

####Usage informations python Prediction_main.py -h usage: Prediction_main.py [-h] -T EDITOR -P PACKAGE -B BEDOUT -O OUTPREFIX Input_file positional arguments: Input_file 40bp(10bp upstream + 20bp sgRNA+3bp PAM + 7bp downstream)(Tab seperate)chr:start-end

optional arguments: -h, --help show this help message and exit -T EDITOR, --Editor EDITOR BASE editor(ABE/CBE/abe/cbe) -P PACKAGE, --Package PACKAGE Package path of BE_Endo -B BEDOUT, --BEDOUT BEDOUT Output BED file for intersection -O OUTPREFIX, --Outprefix OUTPREFIX Outfile prefix to store effiency and propotion result -E ENDOGENOUS, --Endogenous ENDOGENOUS Choose one of endogenous factor name:expression methylation Dnase H3K27ac H3K4me3 PII H3K4me1 CTCF H3K36me3'

Main code "Prediction_main.py" offers two Prediction Mode: First: Default Prediction Mode. This Mode includes prediction using models: BE_Seq and BE_Endo model. example: python Prediction_main.py -T CBE -P /home/wull01 -B $PWD/test1.bed -O $PWD/test/test1_ test_input

output:

1. Predicted BE_Seq eff/proportion table
2. Predicted BE_Endo eff/proportion table

Second: Customizing Prediction Mode. This Mode includes prediction using user provided endogenous factor selected from "expression methylation Dnase H3K27ac H3K4me3 PII H3K4me1 CTCF H3K36me3". example: python Prediction_main.py -T CBE -P /home/wull01 -B $PWD/test1.bed -O $PWD/test/CBE_custize_methylation -E methylation test_input

output:

1. Predicted single factor BE_Endo eff/proportion table

Notice: Here Package "BE_Endo" in the director "/home/wull01"

Input file detailed format TCCAGGCCAGGCAGTCAAGGAAGAAGCCCTGGGCTCCCAG chr14:24431547-24431567 #input 40bp Composition TCCAGGCCAG GCAGTCAAGGAAGAAGCCCT GGG CTCCCAG
|10bp up | | protospacer ||PAM| | 7bp |

####Error fix 1) PermissionError: [Errno 13] Permission denied: 'BD_intersect.sh' chmod a+x BD_intersect.sh

Traceback (most recent call last): File "XXX/BE_Endo/Main/Prediction_main.py", line 19, in PIP_F.pip_file(args.Input_file,args.Editor,args.BEDOUT,args.Package,args.Outprefix) File "XXX/BE_Endo/Main/File_input_main.py", line 58, in pip_file Model_prepare_obj.read_ins("{}/BE_Endo/Main/Intersection_temp/{}".format(workdir,tmpname)) File "/home/wull01/ACBE_endomodel_reanalysis/BE_Endo/BE_endo_Pack/Preprocess/Preprocessing.py", line 94, in read_ins result=pd.read_csv(intersected_path,sep="\t",header=None) File "/home/wull01/anaconda3/envs/py3.8/lib/python3.9/site-packages/pandas/io/parsers.py", line 610, in read_csv return _read(filepath_or_buffer, kwds) File "/home/wull01/anaconda3/envs/py3.8/lib/python3.9/site-packages/pandas/io/parsers.py", line 462, in _read parser = TextFileReader(filepath_or_buffer, **kwds) File "/home/wull01/anaconda3/envs/py3.8/lib/python3.9/site-packages/pandas/io/parsers.py", line 819, in init self._engine = self._make_engine(self.engine) File "/home/wull01/anaconda3/envs/py3.8/lib/python3.9/site-packages/pandas/io/parsers.py", line 1050, in _make_engine return mapping[engine](self.f, **self.options) # type: ignore[call-arg] File "/home/wull01/anaconda3/envs/py3.8/lib/python3.9/site-packages/pandas/io/parsers.py", line 1898, in init self._reader = parsers.TextReader(self.handles.handle, **kwds) File "pandas/_libs/parsers.pyx", line 521, in pandas._libs.parsers.TextReader.cinit pandas.errors.EmptyDataError: No columns to parse from file

Means our endo_factors.bed Does Not put to the right directory Endo BED file download In directory endo_factors, There is a "endo_factors.bed" file (endo_factors/endo_factors.bed). The "endo_factors.bed" is shared via Pan.baidu: "https://pan.baidu.com/s/1wXlLXSgPXN4tdgTqgq8DeQ" with extraction code: "endo" One downloaded, extracted from zip file and put "endo_factors.bed" in the director "endo_factors".

No such file or directory:XXXXX/BD_intersect.sh Change the interpreter of BD_intersect.sh to your own bash interpreter. Such as in MAC, "#!/bin/env bash" is a bad interpreter.Changed to "#!/bin/bash"

Traceback (most recent call last): File "/home/wull01/BE_Endo/Main/Prediction_main.py", line 6, in import File_input_main as PIP_F File "/home/wull01/BE_Endo/Main/File_input_main.py", line 7, in import BE_endo_Pack.Preprocess.Preprocessing as Prepro ModuleNotFoundError: No module named 'BE_endo_Pack'

export PYTHONPATH=$PYTHONPATH:/home/wull01/BE_Endo