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BaselAbujamous / clust

Automatic and optimised consensus clustering of one or more heterogeneous datasets
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ValueError during concatenation in output.py script #81

Open SuvratK opened 7 months ago

SuvratK commented 7 months ago

Hello, I tried to run clust as follows clust unnorm_TPM_abundance.txt -r replicates_file_for_clust.txt -o clust_output But it throws an error in the output.py script "ValueError: all the input array dimensions except for the concatenation axis must match exactly, but along dimension 1, the array at index 0 has size 9 and the array at index 1 has size 8".
I could not figure out if the problem was with the input files or something else. Any help is much appreciated. This is the format of my input files Data file:

IDs ACO27   ACI27   ACO24   ACI24   ACO25   ACI25   ACO28   ACI28   ACO23   ACI23   ACO26   ACI26   ACO15   ACI15   ACO17   ACI17   ACO21   ACI21   ACO13   ACI13   ACO14   ACI14   ACO16   ACI16
TRINITY_DN12488_c0_g1_i1    20.410835   15.087338   12.180356   20.689961   25.098941   18.310295   22.990991   24.790974   28.37162    18.938075   31.466777   39.643565   4.427401    1.182069    1.059718    0.567836    1.378234    3.061071    0   1.864431    0   1.192739    0   2.198282
TRINITY_DN12477_c0_g1_i5    23.736233   26.439388   37.23598    25.095917   34.369804   31.741829   26.106344   25.112859   23.613285   24.386021   25.799767   25.014237   22.453038   30.314432   21.906057   25.520188   38.26372    24.539333   31.125408   23.001255   26.52094    19.962209   20.944755   16.358531
...

Replicates file:

unnorm_TPM_abundance.txt    I3  ACI27   ACI24   ACI25
unnorm_TPM_abundance.txt    O3  ACO27   ACO24   ACO25
unnorm_TPM_abundance.txt    I5  ACI28   ACI23   ACI26
unnorm_TPM_abundance.txt    O5  ACI28   ACI23   ACI26
unnorm_TPM_abundance.txt    I12 ACI15   ACI17   ACI21
unnorm_TPM_abundance.txt    O12 ACO15   ACO17   ACO21
unnorm_TPM_abundance.txt    I18 ACI13   ACI14   ACI16
unnorm_TPM_abundance.txt    O18 ACO13   ACO14   ACO16

This is the entire console output: 

/===========================================================================\
|                                   Clust                                   |
|    (Optimised consensus clustering of multiple heterogenous datasets)     |
|           Python package version 1.18.0 (2022) Basel Abu-Jamous           |
+---------------------------------------------------------------------------+
| Analysis started at: Monday 08 January 2024 (11:00:49)                    |
| 1. Reading dataset(s)                                                     |
| 2. Data pre-processing                                                    |
|  - Automatic normalisation mode (default in v1.7.0+).                     |
|    Clust automatically normalises your dataset(s).                        |
|    To switch it off, use the `-n 0` option (not recommended).             |
|    Check https://github.com/BaselAbujamous/clust for details.             |
|  - Flat expression profiles filtered out (default in v1.7.0+).            |
|    To switch it off, use the --no-fil-flat option (not recommended).      |
|    Check https://github.com/BaselAbujamous/clust for details.             |
Traceback (most recent call last):
  File "/home/kotagal/miniforge3/envs/clust/bin/clust", line 10, in <module>
    sys.exit(main())
             ^^^^^^
  File "/home/kotagal/miniforge3/envs/clust/lib/python3.12/site-packages/clust/__main__.py", line 102, in main
    clustpipeline.clustpipeline(args.datapath, args.m, args.r, args.n, args.o, args.K, args.t,
  File "/home/kotagal/miniforge3/envs/clust/lib/python3.12/site-packages/clust/clustpipeline.py", line 112, in clustpipeline
    Xprocessed = op.processed_X(X_summarised_normalised, conditions, GDM, OGs, MapNew, MapSpecies)  # pandas DataFrames
                 ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
  File "/home/kotagal/miniforge3/envs/clust/lib/python3.12/site-packages/clust/scripts/output.py", line 434, in processed_X
    res[l] = np.concatenate((resHeader[l], res[l]), axis=0)
             ^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
ValueError: all the input array dimensions except for the concatenation axis must match exactly, but along dimension 1, the array at index 0 has size 9 and the array at index 1 has size 8

Thanks,

Suvrat