Hi,
First, thank you very much for developing such a powerful and useful tool.
I’m writing because I find an issue while attempting to run MetaPhlAn 4 in my Conda environment named “metaphlan”. Initially, I was working with my samples, but I consistently received the same error. To troubleshoot, I switched to using the example data provided.
Here’s the command I’m using:
cd /Lola/Example
metaphlan ./SRS014476-Supragingival_plaque.fasta.gz --input_type fasta --index mpa_vJun23_CHOCOPhlAnSGB_202307 --force --bowtie2db /shared/references/metaphlan_db_guix > ./SRS014476-Supragingival_plaque_profile.txt
I’ve specified the database location that works for my colleagues. I’ve also tried downloading the database to my environment and running it from there, but the issue persists.
The error message I’m receiving is as follows:
(ERR): bowtie2-align died with signal 7 (BUS) (core dumped)
Traceback (most recent call last):
File "/Lola/conda/miniconda3/envs/metaphlan/bin/read_fastx.py", line 10, in <module>
sys.exit(main())
^^^^^^
File "/Lola/conda/miniconda3/envs/metaphlan/lib/python3.12/site-packages/metaphlan/utils/read_fastx.py", line 173, in main
f_nreads, f_avg_read_length = read_and_write_raw(f, opened=False, min_len=min_len, prefix_id=prefix_id)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Lola/conda/miniconda3/envs/metaphlan/lib/python3.12/site-packages/metaphlan/utils/read_fastx.py", line 135, in read_and_write_raw
nreads, avg_read_length = read_and_write_raw_int(inf, min_len=min_len, prefix_id=prefix_id)
^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^^
File "/Lola/conda/miniconda3/envs/metaphlan/lib/python3.12/site-packages/metaphlan/utils/read_fastx.py", line 108, in read_and_write_raw_int
_ = sys.stdout.write(
^^^^^^^^^^^^^^^^^
BrokenPipeError: [Errno 32] Broken pipe
I work in a cluster with 32CPU and 503G, so the memory should not be an issue.
I’m particularly puzzled by this persistent error. I have searched for related discussions but haven’t found any that address my specific issue (I apologize if I’ve missed something relevant).
I would greatly appreciate any assistance in resolving this problem. I kindly ask for your understanding if I have misunderstood or overlooked any aspects of this issue.
Thank you in advance for your help and patience!
Lastly, my conda environment looks like this:
name: metaphlan
channels:
- conda-forge
- bioconda
- defaults
dependencies:
- _libgcc_mutex=0.1=conda_forge
- _openmp_mutex=4.5=2_gnu
- _r-mutex=1.0.1=anacondar_1
- _sysroot_linux-64_curr_repodata_hack=3=h69a702a_16
- anyio=4.4.0=pyhd8ed1ab_0
- argcomplete=3.4.0=pyhd8ed1ab_0
- argon2-cffi=23.1.0=pyhd8ed1ab_0
- argon2-cffi-bindings=21.2.0=py312h98912ed_4
- arrow=1.3.0=pyhd8ed1ab_0
- asttokens=2.4.1=pyhd8ed1ab_0
- async-lru=2.0.4=pyhd8ed1ab_0
- attrs=23.2.0=pyh71513ae_0
- babel=2.14.0=pyhd8ed1ab_0
- beautifulsoup4=4.12.3=pyha770c72_0
- binutils_impl_linux-64=2.40=ha1999f0_7
- bioconductor-biobase=2.62.0=r43ha9d7317_2
- bioconductor-biocgenerics=0.48.1=r43hdfd78af_2
- bioconductor-biomformat=1.30.0=r43hdfd78af_0
- bioconductor-biostrings=2.70.1=r43ha9d7317_2
- bioconductor-data-packages=20231203=hdfd78af_0
- bioconductor-genomeinfodb=1.38.1=r43hdfd78af_1
- bioconductor-genomeinfodbdata=1.2.11=r43hdfd78af_1
- bioconductor-iranges=2.36.0=r43ha9d7317_2
- bioconductor-microbiome=1.24.0=r43hdfd78af_0
- bioconductor-multtest=2.58.0=r43ha9d7317_1
- bioconductor-phyloseq=1.46.0=r43hdfd78af_0
- bioconductor-rhdf5=2.46.1=r43hf17093f_1
- bioconductor-rhdf5filters=1.14.1=r43hf17093f_1
- bioconductor-rhdf5lib=1.24.0=r43ha9d7317_2
- bioconductor-s4vectors=0.40.2=r43ha9d7317_2
- bioconductor-xvector=0.42.0=r43ha9d7317_2
- bioconductor-zlibbioc=1.48.0=r43ha9d7317_2
- biom-format=2.1.16=py312h9a8786e_1
- biopython=1.84=py312h9a8786e_0
- blast=2.15.0=pl5321h6f7f691_1
- bleach=6.1.0=pyhd8ed1ab_0
- bowtie2=2.5.4=he20e202_2
- brotli=1.1.0=hd590300_1
- brotli-bin=1.1.0=hd590300_1
- brotli-python=1.1.0=py312h30efb56_1
- bwidget=1.9.14=ha770c72_1
- bzip2=1.0.8=hd590300_5
- c-ares=1.32.1=h4bc722e_0
- ca-certificates=2024.7.4=hbcca054_0
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- contourpy=1.2.1=py312h8572e83_0
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- debugpy=1.8.2=py312h7070661_0
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- dendropy=5.0.1=pyhdfd78af_0
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- entrez-direct=22.1=he881be0_0
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- h5py=3.11.0=nompi_py312hb7ab980_102
- harfbuzz=9.0.0=hfac3d4d_0
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- jupyter-lsp=2.2.5=pyhd8ed1ab_0
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- jupyter_core=5.7.2=py312h7900ff3_0
- jupyter_events=0.10.0=pyhd8ed1ab_0
- jupyter_server=2.14.1=pyhd8ed1ab_1
- jupyter_server_terminals=0.5.3=pyhd8ed1ab_0
- jupyterlab=4.2.3=pyhd8ed1ab_0
- jupyterlab_pygments=0.3.0=pyhd8ed1ab_1
- jupyterlab_server=2.27.2=pyhd8ed1ab_0
- kernel-headers_linux-64=3.10.0=h4a8ded7_16
- keyutils=1.6.1=h166bdaf_0
- kiwisolver=1.4.5=py312h8572e83_1
- krb5=1.21.3=h659f571_0
- lcms2=2.16=hb7c19ff_0
- ld_impl_linux-64=2.40=hf3520f5_7
- lerc=4.0.0=h27087fc_0
- libaec=1.1.3=h59595ed_0
- libasprintf=0.22.5=h661eb56_2
- libasprintf-devel=0.22.5=h661eb56_2
- libblas=3.9.0=22_linux64_openblas
- libbrotlicommon=1.1.0=hd590300_1
- libbrotlidec=1.1.0=hd590300_1
- libbrotlienc=1.1.0=hd590300_1
- libcblas=3.9.0=22_linux64_openblas
- libcurl=8.8.0=hca28451_1
- libdeflate=1.20=hd590300_0
- libedit=3.1.20191231=he28a2e2_2
- libev=4.33=hd590300_2
- libexpat=2.6.2=h59595ed_0
- libffi=3.4.2=h7f98852_5
- libgcc-devel_linux-64=14.1.0=h5d3d1c9_100
- libgcc-ng=14.1.0=h77fa898_0
- libgettextpo=0.22.5=h59595ed_2
- libgettextpo-devel=0.22.5=h59595ed_2
- libgfortran-ng=14.1.0=h69a702a_0
- libgfortran5=14.1.0=hc5f4f2c_0
- libglib=2.80.2=hf974151_0
- libgomp=14.1.0=h77fa898_0
- libhwloc=2.11.1=default_hecaa2ac_1000
- libiconv=1.17=hd590300_2
- libidn2=2.3.7=hd590300_0
- libjpeg-turbo=3.0.0=hd590300_1
- liblapack=3.9.0=22_linux64_openblas
- libnghttp2=1.58.0=h47da74e_1
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- libsanitizer=14.1.0=hcba0ae0_0
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- libsqlite=3.46.0=hde9e2c9_0
- libssh2=1.11.0=h0841786_0
- libstdcxx-devel_linux-64=14.1.0=h5d3d1c9_100
- libstdcxx-ng=14.1.0=hc0a3c3a_0
- libtiff=4.6.0=h1dd3fc0_3
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- libuuid=2.38.1=h0b41bf4_0
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- libxml2=2.12.7=hc051c1a_1
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- matplotlib-base=3.9.1=py312h9201f00_0
- matplotlib-inline=0.1.7=pyhd8ed1ab_0
- metaphlan=4.1.1=pyhdfd78af_0
- mistune=3.0.2=pyhd8ed1ab_0
- mpfr=4.2.1=h9458935_1
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- ncurses=6.5=h59595ed_0
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prefix: /Lola/conda/miniconda3/envs/metaphlan