nextflow run main.nf -profile docker --reads ../../../../../../../home/group_gaurav01/Akash_tab/Nanopore/FAST_P/SO_10645_A_GS_Con1_barcode13_fastp.fastq --db ../../db/16S_ribosomal_RNA --tax ../../db/taxdb/ N E X T F L O W ~ version 22.04.0 Launching main.nf [disturbed_heisenberg] DSL1 - revision: 2a51687d92

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NanoCLUST v1.0dev

Run Name : disturbed_heisenberg Reads : ../../../../../../../home/group_gaurav01/Akash_tab/Nanopore/FAST_P/SO_10645_A_GS_Con1_barcode13_fastp.fastq Max Resources : 128 GB memory, 16 cpus, 10d time per job Container : docker - [:] Output dir : ./results Launch dir : /mnt/USB2/group_gs/Akash/Database/NanoClust/NanoCLUST-master Working dir : /mnt/USB2/group_gs/Akash/Database/NanoClust/NanoCLUST-master/work Script dir : /mnt/USB2/group_gs/Akash/Database/NanoClust/NanoCLUST-master User : group_gaurav01 Config Profile : docker

executor > local (5) [25/8115a7] process > QC (1) [100%] 1 of 1 ✔ [59/d688ab] process > fastqc (1) [100%] 1 of 1 ✔ [97/590a24] process > kmer_freqs (1) [100%] 1 of 1 ✔ [61/ebd5ef] process > read_clustering (1) [ 0%] 0 of 1 [- ] process > split_by_cluster - [- ] process > read_correction - [- ] process > draft_selection - [- ] process > racon_pass - [- ] process > medaka_pass - [- ] process > consensus_classification - [- ] process > join_results - [- ] process > get_abundances - [- ] process > plot_abundances - [05/bd73e4] process > output_documentation [100%] 1 of 1 ✔ Error executing process > 'read_clustering (1)'

Caused by: Process read_clustering (1) terminated with an error exit status (1)

Command executed [/mnt/USB2/group_gs/Akash/Database/NanoClust/NanoCLUST-master/templates/umap_hdbscan.py]:

!/usr/bin/env python

import numpy as np import umap import matplotlib.pyplot as plt from sklearn import decomposition import random import pandas as pd import hdbscan

df = pd.read_csv("freqs.txt", delimiter=" ")

UMAP

motifs = [x for x in df.columns.values if x not in ["read", "length"]] X = df.loc[:,motifs] X_embedded = umap.UMAP(n_neighbors=15, min_dist=0.1, verbose=2).fit_transform(X)

df_umap = pd.DataFrame(X_embedded, columns=["D1", "D2"]) umap_out = pd.concat([df["read"], df["length"], df_umap], axis=1)

HDBSCAN

X = umap_out.loc[:,["D1", "D2"]] umap_out["bin_id"] = hdbscan.HDBSCAN(min_cluster_size=int(50), cluster_selection_epsilon=int(0.5)).fit_predict(X)

PLOT

plt.figure(figsize=(20,20)) plt.scatter(X_embedded[:, 0], X_embedded[:, 1], c=umap_out["bin_id"], cmap='Spectral', s=1) plt.xlabel("UMAP1", fontsize=18) plt.ylabel("UMAP2", fontsize=18) plt.gca().set_aspect('equal', 'datalim') plt.title("Projecting " + str(len(umap_out['bin_id'])) + " reads. " + str(len(umap_out['bin_id'].unique())) + " clusters generated by HDBSCAN", fontsize=18)

for cluster in np.sort(umap_out['bin_id'].unique()): read = umap_out.loc[umap_out['bin_id'] == cluster].iloc[0] plt.annotate(str(cluster), (read['D1'], read['D2']), weight='bold', size=14)

plt.savefig('hdbscan.output.png') umap_out.to_csv("hdbscan.output.tsv", sep=" ", index=False)

Command exit status: 1

Command output: (empty)

Command error: aa2745a0cb3e: Pulling fs layer d770858aae07: Verifying Checksum d770858aae07: Download complete d770858aae07: Pull complete b0f5716385b6: Verifying Checksum b0f5716385b6: Download complete b0f5716385b6: Pull complete 6a1ff24c174d: Verifying Checksum 6a1ff24c174d: Download complete 6a1ff24c174d: Pull complete aa2745a0cb3e: Verifying Checksum aa2745a0cb3e: Download complete aa2745a0cb3e: Pull complete Digest: sha256:7f7561518ea9118613c2082a9fc77aa45fab375a43f77d15cb415631d3ffc600 Status: Downloaded newer image for hecrp/nanoclust-read_clustering:latest Traceback (most recent call last): File "/opt/conda/envs/read_clustering/lib/python3.8/site-packages/numba/core/caching.py", line 487, in save data_name = overloads[key] KeyError: ('f4(f4[::1],f4[::1])', ('x86_64-unknown-linux-gnu', 'sandybridge', '+64bit,-adx,+aes,-avx,-avx2,-avx512bf16,-avx512bitalg,-avx512bw,-avx512cd,-avx512dq,-avx512er,-avx512f,-avx512ifma,-avx512pf,-avx512vbmi,-avx512vbmi2,-avx512vl,-avx512vnni,-avx512vpopcntdq,-bmi,-bmi2,-cldemote,-clflushopt,-clwb,-clzero,+cmov,+cx16,+cx8,-eexecutor > local (5) [25/8115a7] process > QC (1) [100%] 1 of 1 ✔ [59/d688ab] process > fastqc (1) [100%] 1 of 1 ✔ [97/590a24] process > kmer_freqs (1) [100%] 1 of 1 ✔ [61/ebd5ef] process > read_clustering (1) [100%] 1 of 1, failed: 1 ✘ [- ] process > split_by_cluster - [- ] process > read_correction - [- ] process > draft_selection - [- ] process > racon_pass - [- ] process > medaka_pass - [- ] process > consensus_classification - [- ] process > join_results - [- ] process > get_abundances - [- ] process > plot_abundances - [05/bd73e4] process > output_documentation [100%] 1 of 1 ✔ Error executing process > 'read_clustering (1)'

Caused by: Process read_clustering (1) terminated with an error exit status (1)

Command executed [/mnt/USB2/group_gs/Akash/Database/NanoClust/NanoCLUST-master/templates/umap_hdbscan.py]:

!/usr/bin/env python

import numpy as np import umap import matplotlib.pyplot as plt from sklearn import decomposition import random import pandas as pd import hdbscan

df = pd.read_csv("freqs.txt", delimiter=" ")

UMAP

motifs = [x for x in df.columns.values if x not in ["read", "length"]] X = df.loc[:,motifs] X_embedded = umap.UMAP(n_neighbors=15, min_dist=0.1, verbose=2).fit_transform(X)

df_umap = pd.DataFrame(X_embedded, columns=["D1", "D2"]) umap_out = pd.concat([df["read"], df["length"], df_umap], axis=1)

HDBSCAN

X = umap_out.loc[:,["D1", "D2"]] umap_out["bin_id"] = hdbscan.HDBSCAN(min_cluster_size=int(50), cluster_selection_epsilon=int(0.5)).fit_predict(X)

PLOT

for cluster in np.sort(umap_out['bin_id'].unique()): read = umap_out.loc[umap_out['bin_id'] == cluster].iloc[0] plt.annotate(str(cluster), (read['D1'], read['D2']), weight='bold', size=14)

plt.savefig('hdbscan.output.png') umap_out.to_csv("hdbscan.output.tsv", sep=" ", index=False)

Command exit status: 1

Command output: (empty)

Command error: aa2745a0cb3e: Pulling fs layer d770858aae07: Verifying Checksum d770858aae07: Download complete d770858aae07: Pull complete b0f5716385b6: Verifying Checksum b0f5716385b6: Download complete b0f5716385b6: Pull complete 6a1ff24c174d: Verifying Checksum 6a1ff24c174d: Download complete 6a1ff24c174d: Pull complete aa2745a0cb3e: Verifying Checksum aa2745a0cb3e: Download complete aa2745a0cb3e: Pull complete Digest: sha256:7f7561518ea9118613c2082a9fc77aa45fab375a43f77d15cb415631d3ffc600 Status: Downloaded newer image for hecrp/nanoclust-read_clustering:latest Traceback (most recent call last): File "/opt/conda/envs/read_clustering/lib/python3.8/site-packages/numba/core/caching.py", line 487, in save data_name = overloads[key] KeyError: ('f4(f4[::1],f4[::1])', ('x86_64-unknown-linux-gnu', 'sandybridge', '+64bit,-adx,+aes,-avx,-avx2,-avx512bf16,-avx512bitalg,-avx512bw,-avx512cd,-avx512dq,-avx512er,-avx512f,-avx512ifma,-avx512pf,-avx512vbmi,-avx512vbmi2,-avx512vl,-avx512vnni,-avx512vpopcntdq,-bmi,-bmi2,-cldemote,-clflushopt,-clwb,-clzero,+cmov,+cx16,+cx8,-enqcmd,-f16c,-fma,-fma4,-fsgsbase,+fxsr,-gfni,-invpcid,-lwp,-lzcnt,+mmx,-movbe,-movdir64b,-movdiri,-mwaitx,+pclmul,-pconfig,-pku,+popcnt,-prefetchwt1,-prfchw,-ptwrite,-rdpid,-rdrnd,-rdseed,-rtm,+sahf,-sgx,-sha,-shstk,+sse,+sse2,+sse3,+sse4.1,+sse4.2,-sse4a,+ssse3,-tbm,-vaes,-vpclmulqdq,-waitpkg,-wbnoinvd,-xop,+xsave,-xsavec,+xsaveopt,-xsaves'), ('0c41297f1f6a9ad7b5e76ac3455427cf5bda8e992eb29997e17af36f3f4e8fbb', 'e3b0c44298fc1c149afbf4c8996fb92427ae41e4649b934ca495991b7852b855'))

During handling of the above exception, another exception occurred:

Traceback (most recent call last): File ".command.sh", line 4, in import umap File "/opt/conda/envs/readclustering/lib/python3.8/site-packages/umap/init.py", line 1, in from .umap import UMAP File "/opt/conda/envs/readclustering/lib/python3.8/site-packages/umap/umap.py", line 54, in from umap.layouts import ( File "/opt/conda/envs/read_clustering/lib/python3.8/site-packages/umap/layouts.py", line 39, in def rdist(x, y): File "/opt/conda/envs/read_clustering/lib/python3.8/site-packages/numba/core/decorators.py", line 218, in wrapper disp.compile(sig) File "/opt/conda/envs/read_clustering/lib/python3.8/site-packages/numba/core/compiler_lock.py", line 32, in _acquire_compile_lock return func(*args, **kwargs) File "/opt/conda/envs/read_clustering/lib/python3.8/site-packages/numba/core/dispatcher.py", line 825, in compile self._cache.save_overload(sig, cres) File "/opt/conda/envs/read_clustering/lib/python3.8/site-packages/numba/core/caching.py", line 671, in save_overload self._save_overload(sig, data) File "/opt/conda/envs/read_clustering/lib/python3.8/site-packages/numba/core/caching.py", line 681, in _save_overload self._cache_file.save(key, data) File "/opt/conda/envs/read_clustering/lib/python3.8/site-packages/numba/core/caching.py", line 496, in save self._save_index(overloads) File "/opt/conda/envs/read_clustering/lib/python3.8/site-packages/numba/core/caching.py", line 545, in _save_index f.write(data) File "/opt/conda/envs/read_clustering/lib/python3.8/contextlib.py", line 120, in exit next(self.gen) File "/opt/conda/envs/read_clustering/lib/python3.8/site-packages/numba/core/caching.py", line 581, in _open_for_write yield f OSError: [Errno 28] No space left on device

Work dir: /mnt/USB2/group_gs/Akash/Database/NanoClust/NanoCLUST-master/work/61/ebd5ef17b84d0833cf0e048da0c72e

Tip: you can replicate the issue by changing to the process work dir and entering the command bash .command.run

[nf-core/nanoclust] Pipeline completed with errors

genomicsITER / NanoCLUST

I Got this error while running Nanoclust? #65

NanoCLUST v1.0dev

!/usr/bin/env python

UMAP

HDBSCAN

PLOT

!/usr/bin/env python

UMAP

HDBSCAN

PLOT