frankligy / deepimmuno Goto Github PK

Hello,

DeepImmuno might just be what I am looking for!
Unfortunately, I cannot clone the project without error, because some file names contain special characters:

new_imgt_scraping/new_imgt/new_imgt/spiders/hla_paratope/HLA-C*0102.json

I am having issues to download the hla_paratope json files because they have an "*" in the file name.

How important are these Files in order to run the code?

If they are really important would it be a possibility to change the file names so that they dont contain any special characters?

Best regards and thank you for sharing!

Hi, thank you for your great job!
But I have a question about the number of indices missing values for certain amino acids.

According to your description in the paper, there are 13 discarded indices, as below. However, when I check the source file of aaindex1, it seems that some missing values were filled by zero but not filled by "NA", such as ”H KOEP990101“, ”H ZASB820101“ and so on, which confuses me.

hi~

running deepimmuno-cnn on mode "multiple" returns this error:

UnboundLocalError: local variable 'encode' referenced before assignment

which can be traced back to line 156 of deepimmuno-cnn.py when running peptide_data_aaindex - specifically when running:

encode_pep = peptide_data_aaindex(peptide,after_pca)

replacing the function peptide_data_aaindex in place solved the issue for me - so instead of running the line above I run instead:

# encode_pep = peptide_data_aaindex(peptide,after_pca)    # [10,12]
    length = len(peptide)
    if length == 10:
        encode = aaindex(peptide,after_pca)
    elif length == 9:
        peptide = peptide[:5] + '-' + peptide[5:]
        encode = aaindex(peptide,after_pca)
    encode = encode.reshape(encode.shape[0], encode.shape[1], -1)
    encode_pep = encode

not sure whether anyone else can replicate this error, but am raising the issue in case this is actually a bug.

thanks for building this tool!

cheers,
Leda

Dear users,

It has been brought to my attention that there's a typo in my paper supplementary regarding the beta prior, so in the supplementary, it said:

But actually, Beta(32,1) is used for positive-high, Beta(30,1) is used for positive-intermediate and positive, it can be seen from the code:

https://github.com/frankligy/DeepImmuno/blob/main/src/immuno3_3.py#L17-L43

def assign_prior(label):
    if label == 'Positive-High':
        return (32,1)   # beta(15,1)   mean=0.93, std = 0.05
    elif label == 'Positive' or label == 'Positive-Intermediate':
        return (30,1)   # beta(10,1)   mean = 0.90  std = 0.08
    elif label == 'Positive-Low':
        return (28,1)    # beta(5,1)   mean = 0.83, std = 0.14
    elif label == 'Negative':
        return (3,3)    # beta(3,4)   mean = 0.42, std = 0.17

I apologize for any confusion caused by that, and please feel free to reach out for any questions!

Sincerely,
Frank