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All the code described in the Lee et al. (2023) paper
I just freshly set up the environment and the version of biopython installed was 1.83 where GC has changed to gc_fraction (since 1.80) - I received the below error and had to force install biopython 1.79 which helped resolve the issue. It did however tell me matplotlib was not available (which might also be unrelated?).
---------------------------------------------------------------------------
ImportError Traceback (most recent call last)
Cell In[1], line 4
2 import Bio
3 from Bio import SeqIO
----> 4 from Bio.SeqUtils import GC
5 from Bio.Seq import Seq
6 from Bio.SeqRecord import SeqRecord
ImportError: cannot import name 'GC' from 'Bio.SeqUtils' (/scicore/home/rueegg/boehm0002/miniconda3/envs/probedesign/lib/python3.9/site-packages/biopython-1.83-py3.9-linux-x86_64.egg/Bio/SeqUtils/__init__.py)
Cell In[23], line 4
2 path='show'
3 test_path=("data1/densiflorus (plastid)- MT740250.1 retained.fasta")
----> 4 BCAWT_auto_test.auto_test(path,test_path)
5 BCAWT_auto_test.auto_check_file(path)
File ~/miniconda3/lib/python3.11/site-packages/BCAWT/BCAWT_auto_test.py:24, in auto_test(path, test_file)
21 from BCAWT import BCAWT
22 file = open(test_file, "r")
---> 24 BCAWT.BCAW(main_fasta_file = [file] , save_path= path, Auto=True)
File ~/miniconda3/lib/python3.11/site-packages/BCAWT/BCAWT.py:34, in BCAW(main_fasta_file, save_path, ref_fasta_file, genetic_code_, Auto)
32 #from Bio.Alphabet import IUPAC
33 from Bio.Seq import Seq
---> 34 from Bio.SeqUtils import GC
35 from Bio.Data import CodonTable
36 #from Bio.Alphabet import generic_dna
ImportError: cannot import name 'GC' from 'Bio.SeqUtils' (/home/u1/miniconda3/lib/python3.11/site-packages/Bio/SeqUtils/init.py)
Running the extract and align sequences cell produces an AttributeError: 'DataFrame' object has no attribute 'append'. As far as I can tell, the requirements specify the pandas version to >=1.1.5, and the .append function is deprecated in pandas 2.0.0. I'm not sure if the best solution is to restrict the pandas version to sub 2.0.0, or change all the instances of df.append in the code. For my use, changing the pandas requirement to pandas==1.1.5 resolved the issue.
I tried to run the preprocessing notebooks on example data from Marco Grillo (Leica 20x organoid dataset). The mipping ran successfully (the expected folders are produced with mipped images), but the leica_OME_tiff function fails with the error below.
Edit: (On ubuntu 22.04)
I followed the manual, except for one part in the environment setup - it does not run with the Python=3.7 argument. Perhaps my above error is due to using a different python version than 3.7?
Screenshot of input datastructure (pre-mip)
post-mip (note that the base2 folder also contains a coords.csv file, which the other base folders do not contain).
Hello,
First, I managed to run through the pre-processing and decoding notebook really smoothly. It was all well annotated so quite easy to follow along.
I'm trying to run the postprocessing notebook now and I've run into a few issues and one question.
For context, I'm running this on our HPC which does not have internet access to download Cellpose models. Working with cellpose I have always had to consider this and point towards the model directory. Despite the notebook running stardist, it tries to download the models so this caused problems (maybe something to keep in mind for similar use cases?) - this was easy to solve for me in past Notebooks (I'm writing an issue to cellpose developers atm since there seems to be a bug...).
The issues I'm encountering otherwise are:
The notebook says that necessary packages are imported, but I got error messages that csbdeep, stardist, tensorflow are missing. Is this deliberate due to local requirements?
I have not played around with stardist as much as with cellpose, but I have the same error as with cellpose (it is trying to download models - again maybe something worth keeping in mind for annotation?).
Now my question:
Have you come across the use case of cell boundary staining in your experiments? This would mean an additional auxilliary-"channel" which I believe is possible to implement in SpaceTX format? We segment muscle fibers so DAPI is only useful for other cell-types and skeletal muscle fibers require cell-boundary staining to identify. Initially I tried to add the cell boundary channel to the dataset definition, but this obviously did not work. Do you already have a solution/work in progress for such a use-case?
Thanks ever so much!
The final step of the PLP_Design notebook throws a KeyError. All previous cells ran successfully. In the attached
example I get the specific_seqs_final from the file, to avoid having to run the 2hr+ preceding cells again; I hope this is the correct file, it at least results in the same error, which seems to be pandas looking for a column "number" (in Lprobe_Ver2..) that doesn't exist. Lprobe_Ver2.csv was copied from the example directory in this repository.
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