chanwkimlab/marcopolo

MarcoPolo is a clustering-free approach to the exploration of bimodally expressed genes along with group information in single-cell RNA-seq data

marcopolo's Issues

A question regarding augmenting HVG with marcopolo

First of all, thank you for the wonderful tool.
I have been working on multiple samples from different developmental time points and was hoping that MarcoPolo could cluster out some of the developing cells with more accuracy.

I am not super familial with the scanpy pipeline and relatively new to the field so please kindly bear with my rudimentary questions.

I was wondering what specific steps are needed to augment HVG from the standard pipeline.
Am I supposed to simply replace .var.highly_variable from the scanpy pipeline with marker_results from MarcoPolo?
Also, if I am working with multiple samples, can I still adopt this process (augmented HVG) for the integrated data set (concatenated anndata)?

Thank you

Run MarcoPolo in local machine with Jupyter Notebook

Hello @chanwkimlab ,

I'm a beginner for Python world. I would like to test your tool for my dataset and from my local machine with Jupyter Notebook. Can you help me with your code? Actually when I try your vignette, I get this error :

AssertionError                            Traceback (most recent call last)
C:\Users\AppData\Local\Temp/ipykernel_2416/4231211302.py in <module>
      5     adata.obs["size_factor"] = norm_factor/norm_factor.mean()
      6     print("size factor was calculated")
----> 7 regression_result = MarcoPolo.run_regression(adata=adata, size_factor_key="size_factor",
      8                          num_threads=8)
      9 # If you use a local machine, you can set `num_threads` to higher than 1 (maybe upto 4), which will speed up the regression a lot. For some reason, num_threads>1 does not seem to work well on colab (maybe due to the the limited RAM).
.
.
.
AssertionError: Torch not compiled with CUDA enabled

Do you have any idea to resolve this issue?

Thanks a lot in advance.

Regards,
Sha

KeyError: 'phenoid' (from generate_report function)

Hi, I greatly thank you for the wonderful software.

I was trying MarcoPolo with my scRNA-seq data,
I found that save_QQscore, save_MarcoPolo function works well,
but "generate_report" function keeps giving me this error

------Drawing figures------
Traceback (most recent call last):
  File "/home/data/.conda/envs/MarcoPolo/lib/python3.7/site-packages/pandas/core/indexes/base.py", line 3080, in get_loc
    return self._engine.get_loc(casted_key)
  File "pandas/_libs/index.pyx", line 70, in pandas._libs.index.IndexEngine.get_loc
  File "pandas/_libs/index.pyx", line 101, in pandas._libs.index.IndexEngine.get_loc
  File "pandas/_libs/hashtable_class_helper.pxi", line 4554, in pandas._libs.hashtable.PyObjectHashTable.get_item
  File "pandas/_libs/hashtable_class_helper.pxi", line 4562, in pandas._libs.hashtable.PyObjectHashTable.get_item
KeyError: 'phenoid'

The above exception was the direct cause of the following exception:

Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "/home/data/MarcoPolo/MarcoPolo_install/MarcoPolo/MarcoPolo/report.py", line 306, in generate_report
    plot_value=exp_data_meta_transformed['phenoid']
  File "/home/data/.conda/envs/MarcoPolo/lib/python3.7/site-packages/pandas/core/frame.py", line 3024, in __getitem__
    indexer = self.columns.get_loc(key)
  File "/home/data/.conda/envs/MarcoPolo/lib/python3.7/site-packages/pandas/core/indexes/base.py", line 3082, in get_loc
    raise KeyError(key) from err
KeyError: 'phenoid'`

when I look at the outputs, "files index.html", "voting.html" and directory "assets" seems to be properly generated,
but directory "plot_image" is empty.
Can you help me resolve this error?

Thank you,

Running without R dependencies

Hi, could you please elaborate on what should be in the directory given as path argument when running MarcoPolo?
If I have a h5ad file produced with Scanpy could I use it as input for the algorithm and therefore skip then R dependencies?

PBMC analysis

Can you make public the code for your PBMC analysis? Or uploading the adata object you use? Trying to run the same code as the tutorial, but using the 3k PBMC dataset from scanpy, is currently causing the code to stall on my system. I've tried downsampling the pbmcs to ~ 400 cells and 1000 genes, ensuring the same columns exist in the .obs for pbmc's as for your example dataset, etc. Mentioning expected runtimes for the PBMC dataset would also be helpful. I'm running on a compute cluster with GPU support, and see no reason for the issues I'm having.

All the best
Wes

Resolve sample batch

Dear authors, Please accept my sincere thanks for providing such a useful tool.
How to solve the sample batch of input counts, and can I use the normalized data for calculation?
Best,
Miller