Comments (5)
Kinggerm
commented on August 12, 2024
Can you attach the complete log file please? I need to see the version information.
from getorganelle.
pollend
commented on August 12, 2024
GetOrganelle v1.6.2a
get_organelle_from_reads.py assembles organelle genomes from genome skimming data.
Find updates in https://github.com/Kinggerm/GetOrganelle and see README.md for more information.
Python 3.6.7 | packaged by conda-forge | (default, Nov 21 2018, 02:32:25) [GCC 4.8.2 20140120 (Red Hat 4.8.2-15)]
Python libs: numpy 1.14.3; sympy 1.3; scipy 1.2.0; psutil 5.4.8
Dependencies: Bowtie2 2.3.5.1; SPAdes 3.13.0; Blast 2.2.30
from getorganelle.
Kinggerm
commented on August 12, 2024
Thanks for adding this. I am doing field work these days and sorry for the i�ntermittent replay.
This is a minor bug. This happened when it failed in disentangling. Usually it should just report failed without error. I just fixed it in 1.6.2b. Please update to the latest version.
BTW, plant mitogenome is usually full of repeats and hard to disentangle. Besides you are using limited dataset for mitogenome. I am afraid of your chance to get the complete mitogenome is limited.
Thanks for reporting this. Let me know if you have further questions.
Jianjun
from getorganelle.
sivajean
commented on August 12, 2024
hi sir,
same problem here,
GetOrganelle v1.6.2e
get_organelle_from_reads.py assembles organelle genomes from genome skimming data.
Find updates in https://github.com/Kinggerm/GetOrganelle and see README.md for more information.
Python 2.7.12 (default, Nov 12 2018, 14:36:49) [GCC 5.4.0 20160609]
Python libs: numpy 1.11.0; sympy 1.5.1; scipy 0.17.0; psutil 3.4.2
Dependencies: Bowtie2 2.3.5.1; SPAdes 3.13.0; Blast 2.2.30
get_organelle_from_reads.py -1 TRI-1_1.fastq -2 TRI-1_2.fastq -o mitochondria_output -R 50 -k 21,45,
65,85,105 -P 1000000 -F embplant_mt
2020-01-17 19:09:22,393 - INFO: Pre-reading fastq ...
2020-01-17 19:09:22,393 - INFO: Estimating reads to use ... (to skip, set '--reduce-reads-for-covera
ge inf')
2020-01-17 19:09:23,136 - INFO: Tasting 100000+100000 reads ...
2020-01-17 19:09:35,943 - INFO: Tasting 500000+500000 reads ...
2020-01-17 19:10:08,596 - INFO: Tasting 2500000+2500000 reads ...
2020-01-17 19:12:44,394 - INFO: Tasting 12500000+12500000 reads ...
GetOrganelle v1.6.2e
get_organelle_from_reads.py assembles organelle genomes from genome skimming data.
Find updates in https://github.com/Kinggerm/GetOrganelle and see README.md for more information.
Python 2.7.12 (default, Nov 12 2018, 14:36:49) [GCC 5.4.0 20160609]
Python libs: numpy 1.11.0; sympy 1.5.1; scipy 0.17.0; psutil 3.4.2
Dependencies: Bowtie2 2.3.5.1; SPAdes 3.13.0; Blast 2.2.30
get_organelle_from_reads.py -1 TRI-1_1.fastq -2 TRI-1_2.fastq -o mitochondria_output -R 50 -k 21,45,
65,85,105 -P 1000000 -F embplant_mt -t 20
2020-01-17 19:16:13,727 - INFO: Pre-reading fastq ...
2020-01-17 19:16:13,727 - INFO: Estimating reads to use ... (to skip, set '--reduce-reads-for-covera
ge inf')
2020-01-17 19:16:14,445 - INFO: Tasting 100000+100000 reads ...
2020-01-17 19:16:24,746 - INFO: Tasting 500000+500000 reads ...
2020-01-17 19:16:48,361 - INFO: Tasting 2500000+2500000 reads ...
2020-01-17 19:18:42,279 - INFO: Tasting 12500000+12500000 reads ...
2020-01-17 19:28:01,239 - INFO: Estimating reads to use finished.
2020-01-17 19:29:32,428 - INFO: Counting read qualities ...
2020-01-17 19:29:32,639 - INFO: Identified quality encoding format = Illumina 1.8+
2020-01-17 19:29:32,642 - INFO: Trimming bases with qualities (0.00%): 33..33 !
2020-01-17 19:29:32,751 - INFO: Mean error rate = 0.0056
2020-01-17 19:29:32,751 - INFO: Counting read lengths ...
2020-01-17 19:31:21,061 - INFO: Mean = 150.0 bp, maximum = 151 bp.
2020-01-17 19:31:21,061 - INFO: Reads used = 34911164+34911164
2020-01-17 19:31:21,061 - INFO: Pre-reading fastq finished.
2020-01-17 19:31:21,061 - INFO: Making seed reads ...
2020-01-17 19:31:21,062 - INFO: Seed bowtie2 index existed!
2020-01-17 19:31:21,062 - INFO: Mapping reads to seed bowtie2 index ...
2020-01-17 19:51:44,440 - INFO: Mapping finished.
2020-01-17 19:51:44,441 - INFO: Seed reads made: mitochondria_output/seed/embplant_mt.initial.fq (86
36086 bytes)
2020-01-17 19:51:44,441 - INFO: Making seed reads finished.
2020-01-17 19:51:44,441 - INFO: Checking seed reads and parameters ...
2020-01-17 19:51:44,441 - INFO: The automatically-estimated parameter(s) do not ensure the best choi
ce(s).
2020-01-17 19:51:44,442 - INFO: If the result graph is not a circular organelle genome,
2020-01-17 19:51:44,442 - INFO: you could adjust the value(s) of '-w'/'-R' for another new run.
2020-01-17 19:51:47,269 - INFO: Pre-assembling mapped reads ...
2020-01-17 19:51:52,220 - INFO: Pre-assembling mapped reads finished.
2020-01-17 19:51:52,220 - INFO: Estimated embplant_mt-hitting base-coverage = 49.54
2020-01-17 19:51:52,221 - INFO: Estimated word size(s): 85
2020-01-17 19:51:52,221 - INFO: Setting '-w 85'
2020-01-17 19:51:52,221 - INFO: Setting '--max-extending-len inf'
2020-01-17 19:51:52,334 - INFO: Checking seed reads and parameters finished.
2020-01-17 19:51:52,335 - INFO: Making read index ...
2020-01-17 20:12:04,505 - INFO: Mem 11.147 G, 66731260 candidates in all 69822328 reads
2020-01-17 20:12:04,826 - INFO: Pre-grouping reads ...
2020-01-17 20:12:04,826 - INFO: Setting '--pre-w 85'
2020-01-17 20:12:15,712 - INFO: Mem 11.871 G, 1000000/2599095 used/duplicated
2020-01-17 20:17:03,825 - INFO: Mem 29.056 G, 42771 groups made.
2020-01-17 20:17:19,278 - INFO: Making read index finished.
2020-01-17 20:17:21,087 - INFO: Extending ...
2020-01-17 20:17:21,092 - INFO: Adding initial words ...
2020-01-17 20:17:22,831 - INFO: AW 852868
2020-01-17 20:31:27,704 - INFO: Round 1: 66731260/66731260 AI 2111771 AW 50639688 Mem 18.295
2020-01-17 20:52:29,253 - INFO: Round 2: 66731260/66731260 AI 11848345 AW 237069260 Mem 48.236
2020-01-17 21:08:59,068 - INFO: Round 3: 66731260/66731260 AI 15071024 AW 305249294 Mem 56.626
2020-01-17 21:23:59,802 - INFO: Round 4: 66731260/66731260 AI 16312433 AW 337211070 Mem 60.559
2020-01-17 21:39:52,662 - INFO: Round 5: 66731260/66731260 AI 17091449 AW 359373318 Mem 71.286
2020-01-17 21:54:13,421 - INFO: Round 6: 66731260/66731260 AI 17700890 AW 377333402 Mem 73.496
2020-01-17 22:08:38,370 - INFO: Round 7: 66731260/66731260 AI 18206429 AW 392512646 Mem 75.364
2020-01-17 22:23:03,493 - INFO: Round 8: 66731260/66731260 AI 18647628 AW 405543156 Mem 76.968
2020-01-17 22:37:29,216 - INFO: Round 9: 66731260/66731260 AI 19005017 AW 416308600 Mem 78.292
2020-01-17 22:51:54,407 - INFO: Round 10: 66731260/66731260 AI 19317951 AW 425656550 Mem 79.443
2020-01-17 23:06:21,378 - INFO: Round 11: 66731260/66731260 AI 19578733 AW 433396962 Mem 80.395
2020-01-17 23:20:47,656 - INFO: Round 12: 66731260/66731260 AI 19794676 AW 439862562 Mem 81.191
2020-01-17 23:35:14,325 - INFO: Round 13: 66731260/66731260 AI 19977022 AW 445369768 Mem 81.868
2020-01-17 23:49:42,285 - INFO: Round 14: 66731260/66731260 AI 20134016 AW 450133328 Mem 82.455
2020-01-18 00:04:12,082 - INFO: Round 15: 66731260/66731260 AI 20278283 AW 454351896 Mem 82.974
2020-01-18 00:18:39,727 - INFO: Round 16: 66731260/66731260 AI 20397571 AW 457920316 Mem 83.413
2020-01-18 00:33:11,316 - INFO: Round 17: 66731260/66731260 AI 20500786 AW 461007838 Mem 83.793
2020-01-18 00:47:44,921 - INFO: Round 18: 66731260/66731260 AI 20591497 AW 463730994 Mem 84.128
2020-01-18 01:02:16,086 - INFO: Round 19: 66731260/66731260 AI 20670959 AW 466101628 Mem 84.42
2020-01-18 01:16:45,213 - INFO: Round 20: 66731260/66731260 AI 20739246 AW 468148722 Mem 84.671
2020-01-18 01:31:14,642 - INFO: Round 21: 66731260/66731260 AI 20796855 AW 469872910 Mem 84.884
2020-01-18 01:45:45,935 - INFO: Round 22: 66731260/66731260 AI 20845479 AW 471337726 Mem 85.064
2020-01-18 02:00:18,946 - INFO: Round 23: 66731260/66731260 AI 20887037 AW 472603918 Mem 85.22
2020-01-18 02:14:49,355 - INFO: Round 24: 66731260/66731260 AI 20924539 AW 473716602 Mem 85.357
2020-01-18 02:29:19,394 - INFO: Round 25: 66731260/66731260 AI 20956481 AW 474669186 Mem 85.474
2020-01-18 02:43:47,960 - INFO: Round 26: 66731260/66731260 AI 20983448 AW 475478094 Mem 85.573
2020-01-18 02:58:17,909 - INFO: Round 27: 66731260/66731260 AI 21007228 AW 476195906 Mem 85.662
2020-01-18 03:12:46,319 - INFO: Round 28: 66731260/66731260 AI 21027656 AW 476806976 Mem 85.737
2020-01-18 03:27:15,438 - INFO: Round 29: 66731260/66731260 AI 21044963 AW 477335980 Mem 85.802
2020-01-18 03:41:44,039 - INFO: Round 30: 66731260/66731260 AI 21059804 AW 477785318 Mem 85.857
2020-01-18 03:56:20,079 - INFO: Round 31: 66731260/66731260 AI 21073306 AW 478187074 Mem 85.907
2020-01-18 04:10:52,934 - INFO: Round 32: 66731260/66731260 AI 21084984 AW 478537110 Mem 85.95
2020-01-18 04:25:22,488 - INFO: Round 33: 66731260/66731260 AI 21095274 AW 478842516 Mem 85.987
2020-01-18 04:39:54,564 - INFO: Round 34: 66731260/66731260 AI 21103810 AW 479094300 Mem 86.018
2020-01-18 04:54:28,559 - INFO: Round 35: 66731260/66731260 AI 21111484 AW 479320006 Mem 86.046
2020-01-18 05:09:04,232 - INFO: Round 36: 66731260/66731260 AI 21118203 AW 479518396 Mem 86.071
2020-01-18 05:23:45,891 - INFO: Round 37: 66731260/66731260 AI 21124226 AW 479691684 Mem 86.092
2020-01-18 05:38:40,497 - INFO: Round 38: 66731260/66731260 AI 21129486 AW 479846954 Mem 86.111
2020-01-18 05:53:23,392 - INFO: Round 39: 66731260/66731260 AI 21134542 AW 479997576 Mem 86.13
2020-01-18 06:08:04,157 - INFO: Round 40: 66731260/66731260 AI 21139428 AW 480134720 Mem 86.146
2020-01-18 06:23:02,448 - INFO: Round 41: 66731260/66731260 AI 21143585 AW 480257262 Mem 86.162
2020-01-18 06:37:37,908 - INFO: Round 42: 66731260/66731260 AI 21147249 AW 480363942 Mem 86.175
2020-01-18 06:52:16,039 - INFO: Round 43: 66731260/66731260 AI 21150572 AW 480461710 Mem 86.187
2020-01-18 07:06:52,671 - INFO: Round 44: 66731260/66731260 AI 21153480 AW 480547598 Mem 86.197
2020-01-18 07:21:33,310 - INFO: Round 45: 66731260/66731260 AI 21156331 AW 480630836 Mem 86.207
2020-01-18 07:36:11,084 - INFO: Round 46: 66731260/66731260 AI 21158824 AW 480704762 Mem 86.217
2020-01-18 07:50:53,511 - INFO: Round 47: 66731260/66731260 AI 21161162 AW 480772628 Mem 86.225
2020-01-18 08:05:38,382 - INFO: Round 48: 66731260/66731260 AI 21163145 AW 480828960 Mem 86.232
2020-01-18 08:20:19,731 - INFO: Round 49: 66731260/66731260 AI 21164988 AW 480882744 Mem 86.238
2020-01-18 08:34:55,895 - INFO: Round 50: 66731260/66731260 AI 21166712 AW 480934038 Mem 86.245
2020-01-18 08:34:55,895 - INFO: Hit the round limit 50 and terminated ...
2020-01-18 10:10:14,276 - INFO: Extending finished.
2020-01-18 10:10:16,882 - INFO: Separating filtered fastq file ...
2020-01-18 10:12:49,096 - INFO: Setting '-k 21,45,65,85,105'
2020-01-18 10:12:49,096 - INFO: Assembling using SPAdes ...
2020-01-18 17:42:46,852 - INFO: Insert size = 551.987, deviation = 134.982, left quantile = 392, rig
ht quantile = 724
2020-01-18 17:42:46,853 - INFO: Assembling finished.
2020-01-18 17:42:46,853 - INFO: Slimming assembly graphs ...
2020-01-18 18:32:48,819 - INFO: Slimming mitochondria_output/filtered_spades/K105/assembly_graph.fas
tg finished!
2020-01-18 19:29:59,499 - INFO: Slimming mitochondria_output/filtered_spades/K85/assembly_graph.fast
g finished!
2020-01-18 22:36:19,256 - INFO: Slimming mitochondria_output/filtered_spades/K65/assembly_graph.fast
g finished!
2020-01-19 04:33:15,218 - INFO: Slimming mitochondria_output/filtered_spades/K45/assembly_graph.fast
g finished!
2020-01-19 04:33:15,219 - INFO: Slimming assembly graphs finished
2020-01-19 04:33:15,219 - INFO: Extracting embplant_mt from the assemblies ...
2020-01-19 04:33:15,220 - INFO: Disentangling mitochondria_output/filtered_spades/K105/assembly_grap
h.fastg.extend-embplant_mt-embplant_pt.fastg as a circular genome ...
2020-01-19 04:43:15,220 - INFO: Disentangling timeout. (see '--disentangle-time-limit' for more)
2020-01-19 04:43:15,220 - INFO: Disentangling mitochondria_output/filtered_spades/K85/assembly_graph
.fastg.extend-embplant_mt-embplant_pt.fastg as a circular genome ...
2020-01-19 04:53:24,200 - INFO: Disentangling timeout. (see '--disentangle-time-limit' for more)
2020-01-19 04:53:24,202 - INFO: Disentangling mitochondria_output/filtered_spades/K65/assembly_graph
.fastg.extend-embplant_mt-embplant_pt.fastg as a circular genome ...
2020-01-19 05:03:36,534 - INFO: Disentangling timeout. (see '--disentangle-time-limit' for more)
2020-01-19 05:03:36,535 - INFO: Disentangling mitochondria_output/filtered_spades/K45/assembly_graph
.fastg.extend-embplant_mt-embplant_pt.fastg as a circular genome ...
2020-01-19 05:14:18,106 - INFO: Disentangling timeout. (see '--disentangle-time-limit' for more)
2020-01-19 05:14:18,109 - INFO: Disentangling mitochondria_output/filtered_spades/K105/assembly_grap
h.fastg.extend-embplant_mt-embplant_pt.fastg as contig(s) ...
2020-01-19 06:15:32,389 - INFO: Disentangling timeout. (see '--disentangle-time-limit' for more)
2020-01-19 06:15:32,393 - INFO: Disentangling mitochondria_output/filtered_spades/K85/assembly_graph
.fastg.extend-embplant_mt-embplant_pt.fastg as contig(s) ...
2020-01-19 07:15:42,389 - INFO: Disentangling timeout. (see '--disentangle-time-limit' for more)
2020-01-19 07:15:42,395 - INFO: Disentangling mitochondria_output/filtered_spades/K65/assembly_graph
.fastg.extend-embplant_mt-embplant_pt.fastg as contig(s) ...
2020-01-19 08:15:56,728 - INFO: Disentangling timeout. (see '--disentangle-time-limit' for more)
2020-01-19 08:15:56,730 - INFO: Disentangling mitochondria_output/filtered_spades/K45/assembly_graph
.fastg.extend-embplant_mt-embplant_pt.fastg as contig(s) ...
2020-01-19 09:16:38,141 - INFO: Disentangling timeout. (see '--disentangle-time-limit' for more)
2020-01-19 09:16:38,141 - INFO: Please ...
2020-01-19 09:16:38,141 - INFO: load the graph file 'assembly_graph.fastg.extend-embplant_mt-embplan
t_pt.fastg,assembly_graph.fastg' in K105,K85,K65,K45
2020-01-19 09:16:38,141 - INFO: load the CSV file 'assembly_graph.fastg.extend-embplant_mt-embplant_
pt.csv' in K105,K85,K65,K45
2020-01-19 09:16:38,142 - INFO: visualize and export your result in Bandage.
2020-01-19 09:16:38,142 - INFO: If you have questions for us, please provide us with the get_org.log
.txt file and the graph in the format you like!
2020-01-19 09:17:48,156 - INFO: Extracting embplant_mt from the assemblies failed.
Total cost 136894.67 s
Thank you!
Hope you get provide some idea to clear this error
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Kinggerm
commented on August 12, 2024
Hi,
Please take a look at the log file and do as what it suggested. This is not the same problem. pollend opened this issue for detecting a bug.
Rather than a bug, your case is a matter of the complexity of the data, meaning that at the last step GetOrganelle can not export the path automatically because of the complicated assembly graph (data character) and the default --disentangle-time-limit 180.
You could rerun the last step using disentangle_organelle_assembly.py with increased disentangle-time-limit, or do manual completion using Bandage. No matter which option you choose, you should visualize the assembly graph in Bandage first to get an overview of your result (as already suggested in the log file: load the graph file 'assembly_graph.fastg.extend-embplant_mt-embplant_pt.fastg,assembly_graph.fastg' and the CSV file 'assembly_graph.fastg.extend-embplant_mt-embplant_pt.csv'). If you have trouble in interpreting the assembly graph in Bandage, please turn on the depth/length/CSV data and post the image here.
Besides, as the mapping suggested, the mitogenome base coverage might be relatively low (49.54), which is not a good sign. But, anyway, please do visualization first to see how it really goes.
from getorganelle.
Related Issues (20)
- Errors in assembly effect evaluation HOT 3
- error using different seed HOT 1
- Plot assembly coverage? HOT 1
- Baiting for ITS1-5.8S-ITS2 ribosomal regions HOT 1
- Error with Mitochondrial Assembly
- Batch works HOT 2
- Error with OS return value: 22; Can anyone please help me with a solution ? HOT 5
- Using the GFA file (p_utg) exported by hifiasm for assembly with the error "Slimming failed." HOT 1
- Running getorganelle with raw target sequencing data error HOT 1
- [IRRELEVANT] Trying to install compas-wood with failed repodata HOT 1
- Repeat of spades issues like #152 and #83 with update to getorganelle v1.7.7.0 HOT 3
- ERROR: Assembling failed due to SPAdes failure HOT 4
- More sequence.fasta？
- strand + or - ? HOT 1
- Issue : Invalid characters # Whitespace not allowed HOT 2
- Using embplant_mt and embplant_pt not possible HOT 2
- GetOrganelle aborts with error ("Killed") HOT 3
- Problems with canu-produced gfa processing HOT 1
- Program killed during early extension; RAM issue unlikely HOT 2
- ERROR: slimming the pre-assembled graph failed
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