Team:SJTU-BioX-Shanghai/Software
Off-Target Predictor
Why we need this software?
Although we develop a method to calculate the probablities of off-target, the work ammount is still unacceptable when we take genome size into account.
Just for the BL21(DE3) we use, the genome size is 4.3Mbp, facing such enormous genome, it's unbelievable to find lure site by hand. Therefore, it's vital for us to build a software to automatically find lure sites can calculate their off-target probablities.
We built a software to find all lure sites and calculate their probablities based on our model. We want our software not only be limited to E. coli, but can also be applied to other genome, such as GRCh38(3.1Bbp). So we used C language, which is known for high effienciency, to build our software.
It is to be noticed that we used BL21(DE3) as our software's default reference genome. But it could be changed by replacing the genome file named as A.fa to software's directory. Our model is compatible for Cas9 system.
Instruction
Install
Download the file, click Here, or from https://github.com/JimmyZhu1999/iGEM-offtar
Unzip the file
Data input
Run 1_5.exe
First type in the first eleven bases of target sequence
Then type in the latter nine bases of target sequence
Floor setting
Just like we have mentioned before, find the lure sequences and pick our the target sequence with high probability of off target is a vital work. In order to find lure site with high probability, we allow the user to set the floor of scanning and find vital lure site in their definition.
Data output
We will output our result with important information:
Number of lure
Place of lure
Lure sequence
Off-target probablity
Then we will repeat the procerss on the other strand
Biostorage Codec
Why we need this software
We achieve the highest fault tolerance with minimal redundancy by encoding our data to Galois field and decoding them with Reed-Soloman algorithm. However, such calculations are very large for researchers, so we need to develop a codec to encode the data into a 96-well plate and read the 96-well plate and decode it into the data we need.
What's more, in a practical way, with panels seeded with our engineered bacteria, information transformed into QR-code can be recorded by adding inducer to dots that are black. Information can be easily extract by scanning the plate by a microplate reader.
Instruction
Install
Download the file, click Here,or from https://github.com/JimmyZhu1999/iGEM-codec
Unzip the file
Our software require Python 3.7 to run, together with packages xlrd. You can download Python3.7 from Here
(https://www.python.org/downloads/release/python-375/)
Encode
Run ncoder.py
Input the data to be stored
Find image file in the subfolder '/mircoplate' where the file is located
The software will encode data and output the image that will instruct you to add inducer to the 96-well plate.
Sample image:
and
Decode
After induction,put 96-well plate under microplate reader and read fluorescence and then read OD600(emission at 485nm and excitation at 528nm)
Name the data "data.xls"
The decoded data will be shown in the window
We use 96-well plate to store the data and we successfully decode the data
Our 96-well plate image can be seen Here
We also examined the corrupted data, and the result show we can correct the error:
The corrupted image is:
and
SJTU-BioX-Shanghai
Contact us: sjtuigem@gmail.com
Bio-X Institute, Shanghai Jiao Tong University, Dongchuan Rd. 800