"sc.pp.neighbors" kills kernel

At the stage of finding neighbors, my jupyter kept showing this error: Screen Shot 2022-10-22 at 2 51 46 PM

the error:

OMP: Info #276: omp_set_nested routine deprecated, please use omp_set_max_active_levels instead.
And it killed the kernel entirely.

I try to make this work by running this in Linux but it got killed again. Screen Shot 2022-10-22 at 3 13 47 PM

Below is my basic workflow:

def pp(adata):
    sc.pp.filter_cells(adata, min_genes=200) #get rid of cells with fewer than 200 genes
    sc.pp.filter_genes(adata, min_cells=3) #get rid of genes that are found in fewer than 3 cells
    adata.var['mt'] = adata.var_names.str.startswith('MT-')  # annotate the group of mitochondrial genes as 'mt'
    sc.pp.calculate_qc_metrics(adata, qc_vars=['mt'], percent_top=None, log1p=False, inplace=True)
    upper_lim = np.quantile(adata.obs.n_genes_by_counts.values, .98)
    lower_lim = np.quantile(adata.obs.n_genes_by_counts.values, .02)
    adata = adata[(adata.obs.n_genes_by_counts < upper_lim) & (adata.obs.n_genes_by_counts > lower_lim)]
    adata = adata[adata.obs.pct_counts_mt < 25]
    sc.pp.normalize_total(adata, target_sum=1e4) #normalize every cell to 10,000 UMI
    sc.pp.log1p(adata) #change to log counts
    sc.pp.highly_variable_genes(adata, min_mean=0.0125, max_mean=3, min_disp=0.5) #these are default values
    adata.raw = adata #save raw data before processing values and further filtering
    adata = adata[:, adata.var.highly_variable] #filter highly variable
    sc.pp.regress_out(adata, ['total_counts', 'pct_counts_mt']) #Regress out effects of total counts per cell and the percentage of mitochondrial genes expressed
    sc.pp.scale(adata, max_value=10) #scale each gene to unit variance
    sc.tl.pca(adata, svd_solver='arpack')
    sc.pp.neighbors(adata, n_neighbors=10, n_pcs=20)
    sc.tl.umap(adata)
    return adata

adata = sc.read_csv("./myfile.csv", first_column_names=True)
adata = pp(adata)

My computer is Mac book Intel i5.

Thanks!

Versions

anndata 0.8.0 scanpy 1.9.1

OpenSSL 22.0.0 PIL 9.2.0 PyObjCTools NA absl NA appnope 0.1.2 astunparse 1.6.3 attr 21.4.0 backcall 0.2.0 bcrypt 3.2.0 beta_ufunc NA binom_ufunc NA boto3 1.24.28 botocore 1.27.28 bottleneck 1.3.5 brotli NA certifi 2022.09.24 cffi 1.15.1 chardet 4.0.0 charset_normalizer 2.0.4 chex 0.1.5 cloudpickle 2.0.0 colorama 0.4.5 contextlib2 NA cryptography 37.0.1 cycler 0.10.0 cython_runtime NA cytoolz 0.11.0 dask 2022.7.0 dateutil 2.8.2 debugpy 1.5.1 decorator 5.1.1 defusedxml 0.7.1 deprecate 0.3.2 dill 0.3.4 docrep 0.3.2 entrypoints 0.4 etils 0.8.0 flax 0.6.1 fsspec 2022.7.1 google NA graphviz 0.20 h5py 3.7.0 idna 3.4 igraph 0.10.2 ipykernel 6.15.2 ipython_genutils 0.2.0 ipywidgets 7.6.5 jax 0.3.23 jaxlib 0.3.22 jedi 0.18.1 jinja2 2.11.3 jmespath 0.10.0 joblib 1.1.1 jupyter_server 1.18.1 kiwisolver 1.4.2 leidenalg 0.8.10 llvmlite 0.39.1 louvain 0.8.0 lz4 3.1.3 markupsafe 2.0.1 matplotlib 3.5.2 matplotlib_inline 0.1.6 ml_collections NA mpl_toolkits NA msgpack 1.0.3 mudata 0.2.0 multipledispatch 0.6.0 natsort 8.1.0 nbinom_ufunc NA numba 0.56.3 numexpr 2.8.3 numpy 1.22.4 numpyro 0.10.1 opt_einsum v3.3.0 optax 0.1.3 packaging 21.3 pandas 1.4.4 parso 0.8.3 pexpect 4.8.0 pickleshare 0.7.5 pkg_resources NA plotly 5.9.0 prompt_toolkit 3.0.20 psutil 5.9.0 ptyprocess 0.7.0 pydev_ipython NA pydevconsole NA pydevd 2.6.0 pydevd_concurrency_analyser NA pydevd_file_utils NA pydevd_plugins NA pydevd_tracing NA pygments 2.11.2 pyparsing 3.0.9 pyro 1.8.2 pytorch_lightning 1.7.7 pytz 2022.1 regex 2.5.116 requests 2.28.1 rich NA scipy 1.7.3 scvi 0.18.0 session_info 1.0.0 setuptools 63.4.1 simplejson 3.17.6 six 1.16.0 sklearn 1.1.2 snappy NA socks 1.7.1 sphinxcontrib NA storemagic NA tblib 1.7.0 tensorboard 2.9.1 texttable 1.6.4 threadpoolctl 2.2.0 tlz 0.11.0 toolz 0.11.2 torch 1.12.1 torchmetrics 0.10.0 torchvision 0.13.1 tornado 6.1 tqdm 4.64.1 traitlets 5.1.1 tree 0.1.7 typing_extensions NA urllib3 1.26.12 wcwidth 0.2.5 wrapt 1.14.1 yaml 6.0 zipp NA zmq 23.2.0 zope NA

IPython 7.31.1 jupyter_client 7.3.4 jupyter_core 4.11.1 jupyterlab 3.4.4 notebook 6.4.12

Python 3.9.12 (main, Jun 1 2022, 06:36:29) [Clang 12.0.0 ] macOS-10.16-x86_64-i386-64bit

Session information updated at 2022-10-22 15:12

Issue Analytics

State:
Created a year ago
Comments:9 (4 by maintainers)

Top GitHub Comments

1reaction

xinyuejohncommented, Oct 26, 2022

I reinstalled the environment and solved the issue.

0reactions

mxposedcommented, Dec 11, 2022

Has anyone found a solution for this? I run into segfault with the same message when trying to run sc.pp.calculate_qc_metrics on my M2. Latest clean installation. I have the core dump as well, but I don’t know how to get useful information from there.

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