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t-neumann
SlamDunk for smallRNA data
Hello, I have a couple of questions:
- Am I able to use slamdunk with small RNA library? I am trying to see nascent small RNAs using 4SU labelling.
- I am having difficulty with the usage and non of the discussions I have seen have helped my issue. Thank you
@t-neumann
Hi,
- Not really, but there is a paper from the same lab dedicated to small RNAs https://pubmed.ncbi.nlm.nih.gov/31350118/
- What are you having difficulties with?
Thank you for your response.
See my command bellow and the error I get after words.
Command slamdunk all -r PATHTO/genomic.fna -b HE.all.bed -o SLAMDUNK -5 0 -n 100 -t 8 -m -rl 32 PATHTOsamp1.R1_001.fastq PATHTOsamp1.R2_001.fastq PATHTOsamp1.R3_001.fastq PATHTOsamp1.R4_001.fastq PATHTOsamp2.R1_001.fastq PATHTOsamp2.R2_001.fastq PATHTOsamp2.R3_001.fastq PATHTOsamp2.R4_001.fastq
ERRROR MESSAGE
slamdunk all
Running slamDunk map for 8 files (8 threads)
Traceback (most recent call last):
File "/Users/Alex/miniconda3/bin/slamdunk", line 8, in
@t-neumann
Can you go to the map folder and have a look at the log files there - what do they say?
This is what "myfastq.slamdunk_mapped.log" says.
b'/bin/sh: ngm: command not found\n'b'/bin/sh: ngm: command not found\n'
the other map file, "files_slamdunk_mapped.log" is empty
Also I see this in my slamdunk version.py incase you want to see.
Overall slamDunk version
version = "0.4.3"
File format version of BAM files from slamdunk filter
bam_version = "3"
File format version of count files from slamdunk count
count_version = "3"
Required NextGenMap version
ngm_version = "0.5.5"
@t-neumann
Hm how did you install slamdunk? Via conda? Or Docker?
Sounds like NGM was not installed.
Then this is weird, did you set up all channels correctly? What if you redo it like this?
conda config --add channels defaults
conda config --add channels bioconda
conda config --add channels conda-forge
conda create --name slamdunk slamdunk
source activate slamdunk
export PYTHONNOUSERSITE=1
And afterwards run your command?
Then this is weird, did you set up all channels correctly? What if you redo it like this?
conda config --add channels defaults conda config --add channels bioconda conda config --add channels conda-forge conda create --name slamdunk slamdunk source activate slamdunk export PYTHONNOUSERSITE=1And afterwards run your command?
Thank you very much for your help. It started running fine but terminated and produced the following (IN TERMINAL) It also generated 5 sam output instead of 8. Not sure why.
IN TERMINAL
slamdunk all
Running slamDunk map for 8 files (8 threads)
......Traceback (most recent call last):
File "/Users/Alex/miniconda3/envs/slamdunk/bin/slamdunk", line 10, in
@t-neumann
Please do you have any idea why the run is not being completed? and the error? @t-neumann
Sorry lost track of this: Can you let me know if there is anything written in the log files in the map folder?
Thats Ok.
To recap. 5 sam files were made (instead of 8), 5 mapped log files were created alongside. Below is what was written in one of the log files:
b'[MAIN] NextGenMap 0.5.5\n'b'[MAIN] Startup : x64 (build Mar 2 2019 13:21:35)\n'b'[MAIN] Starting time: 2020-12-16.09:46:31\n'b'[CONFIG] Parameter: --affine 0 --argos_min_score 0 --bin_size 2 --block_multiplier 2 --broken_pairs 0 --bs_cutoff 6 --bs_mapping 0 --cpu_threads 8 --dualstrand 1 --fast 0 --fast_pairing 0 --force_rlength_check 0 --format 1 --gap_extend_penalty 5 --gap_read_penalty 20 --gap_ref_penalty 20 --gpu 0 --hard_clip 0 --keep_tags 0 --kmer 13 --kmer_min 0 --kmer_skip 2 --local 1 --match_bonus 10 --match_bonus_tc 2 --match_bonus_tt 10 --max_cmrs 2147483647 --max_equal 1 --max_insert_size 1000 --max_polya 4 --max_read_length 0 --min_identity 0.650000 --min_insert_size 0 --min_mq 0 --min_residues 0.500000 --min_score 0.000000 --mismatch_penalty 15 --mode 0 --no_progress 1 --no_unal 0 --ocl_threads 1 --output SLAMDUNK/map/SeqdataID.fastq_slamdunk_mapped.sam --overwrite 1 --pair_score_cutoff 0.900000 --paired 0 --parse_all 1 --pe_delimiter / --qry /Volumes/MasterBackUp/SeqdataID.fastq.trimmed --qry_count -1 --qry_start 0 --ref /Users/Alex/Downloads/RefGENOMEfna --ref_mode -1 --rg_id 0 --rg_sm SeqdataID.fastq:pulse:0 --sensitive 0 --silent_clip 0 --skip_mate_check 0 --skip_save 0 --slam_seq 2 --step_count 4 --strata 1 --topn 100 --trim5 0 --update_check 0 --very_fast 0 --very_sensitive 0\n'b'[NGM] Opening for output (SAM): SLAMDUNK/map/SeqdataID.fastq_slamdunk_mapped.sam\n'b'[SEQPROV] Reading encoded reference from /Users/Alex/Downloads/RefGENOMEfna-enc.2.ngm\n'b'[SEQPROV] Reading 684 Mbp from disk took 0.16s\n'b'[PREPROCESS] Reading RefTable from /Users/Alex/Downloads/RefGENOMEfna-ht-13-2.3.ngm\n'b'[PREPROCESS] Reading from disk took 0.66s\n'b'[PREPROCESS] Max. k-mer frequency set so 179!\n'b'[INPUT] Input is single end data.\n'b'[INPUT] Opening file /Volumes/MasterBackUp/SeqdataID.fastq.trimmed for reading\n'b'[INPUT] Input is Fastq\n'b'[INPUT] Estimating parameter from data\n'b'[INPUT] Reads found in files: 5064335\n'b'[INPUT] Average read length: 24 (min: 18, max: 34)\n'b'[INPUT] Corridor width: 8\n'b'[INPUT] Average kmer hits pro read: 2.616784\n'b'[INPUT] Max possible kmer hit: 4\n'b'[INPUT] Estimated sensitivity: 0.654196\n'b'[INPUT] Estimating parameter took 2.739s\n'b'[INPUT] Input is Fastq\n'b'[CONFIG] Value gpu : 0 out of range [1, 32] - defaulting to 1\n'b'[CONFIG] No array declared for gpu\n'b'[OPENCL] Available platforms: 1\n'b'[OPENCL] Apple\n'b'[OPENCL] Selecting OpenCl platform: Apple\n'b'[OPENCL] Platform: OpenCL 1.2 (May 24 2018 20:07:03)\n'b'[CONFIG] Value gpu : 0 out of range [1, 32] - defaulting to 1\n'b'[CONFIG] No array declared for gpu\n'b'[CONFIG] Value gpu : 0 out of range [1, 32] - defaulting to 1\n'b'[CONFIG] No array declared for gpu\n'b'[CONFIG] Value gpu : 0 out of range [1, 32] - defaulting to 1\n'b'[CONFIG] No array declared for gpu\n'b'[CONFIG] Value gpu : 0 out of range [1, 32] - defaulting to 1\n'b'[CONFIG] No array declared for gpu\n'b'[CONFIG] Value gpu : 0 out of range [1, 32] - defaulting to 1\n'b'[CONFIG] No array declared for gpu\n'b'[CONFIG] Value gpu : 0 out of range [1, 32] - defaulting to 1\n'b'[CONFIG] No array declared for gpu\n'b'[CONFIG] Value gpu : 0 out of range [1, 32] - defaulting to 1\n'b'[CONFIG] No array declared for gpu\n'b'[OPENCL] Context for GPU devices created.\n'b'[OPENCL] 2 GPU device(s) found: \n'b'[OPENCL] Device 0: AMD Radeon HD - FirePro D300 Compute Engine (Driver: 1.2 (Jun 29 2018 18:33:51))\n'b'[OPENCL] Device 1: AMD Radeon HD - FirePro D300 Compute Engine (Driver: 1.2 (Jun 29 2018 18:33:51))\n'b'[Score (OpenCL)] Releasing pinned memory.\n'b'[Score (OpenCL)] Releasing pinned memory.\n'b'[Score (OpenCL)] Releasing pinned memory.\n'b'[Score (OpenCL)] Releasing pinned memory.\n'b'[Score (OpenCL)] Releasing pinned memory.\n'b'[Score (OpenCL)] Releasing pinned memory.\n'b'[Score (OpenCL)] Releasing pinned memory.\n'b'[Score (OpenCL)] Releasing pinned memory.\n'b'[MAIN] Alignments computed: 23734051\n'b'[MAIN] Done (4841107 reads mapped (95.59%), 223228 reads not mapped, 23920820 lines written)(elapsed: 162.368103s)\n'b'[UPDATE_CHECK] Your version of NGM is more than 6 months old - a newer version may be available. (For performing an automatic check use --update-check)\n'
Ok I suppose the 5 samples worked also because I dont see an error in the log files. Can you try to only run it on the failed samples and see what happens there?
Hello, So I ran the entire slamdunk all command on my magnolia (cloud ) account, the sam files were created, bam files created but not indexed. I am guessing the run is supposed to create indices. Also in the count folder, every file there is empty, while the snp and filter have data in it. How do I create the index and also creat the pdfs please? thanks
@t-neumann
Did you get any error messages for those files? How do the input fastq files look like?
I honestly don't see any error in the log file. However, the run terminated with the following message. Also my fastq files is a regular fastq file (uncompressed).
slamdunk all Running slamDunk map for 8 files (20 threads) ........ Running slamDunk sam2bam for 8 files (20 threads) ........ Running slamDunk filter for 8 files (20 threads) ........
Running slamDunk SNP for 8 files (10 threads)
........
Running slamDunk tcount for 8 files (20 threads)
joblib.externals.loky.process_executor._RemoteTraceback:
"""
Traceback (most recent call last):
File "/home/jopeter/miniconda2/envs/slamdunk/lib/python3.8/site-packages/joblib/externals/loky/process_executor.py", line 431, in _process_worker
r = call_item()
File "/home/jopeter/miniconda2/envs/slamdunk/lib/python3.8/site-packages/joblib/externals/loky/process_executor.py", line 285, in call
return self.fn(*self.args, **self.kwargs)
File "/home/jopeter/miniconda2/envs/slamdunk/lib/python3.8/site-packages/joblib/_parallel_backends.py", line 595, in call
return self.func(*args, **kwargs)
File "/home/jopeter/miniconda2/envs/slamdunk/lib/python3.8/site-packages/joblib/parallel.py", line 262, in call
return [func(*args, **kwargs)
File "/home/jopeter/miniconda2/envs/slamdunk/lib/python3.8/site-packages/joblib/parallel.py", line 262, in
The above exception was the direct cause of the following exception:
Traceback (most recent call last):
File "/home/jopeter/miniconda2/envs/slamdunk/bin/slamdunk", line 10, in
Ok how does your bed file look? Look like there's the strand information missing.
Hello. happy holidays. my bed file looks like this; chr1 17625 17799 174 chr2 19196 19279 83 chr2 134518 134571 53 chr1 441385 441610 225
I tried to add strand information so that they look like this; chr1 17625 17799 174 + chr2 19196 19279 83 - chr2 134518 134571 53 - chr1 441385 441610 225 +
The run still terminated with the error "RuntimeError: Input BED file does not contain stranded intervals."
Am I doing it wrong? is there another way to add thE strand info?
@t-neumann
Yes you miss the score column after the gene id - check out the official bed format. you can put the score to 1000, slamdunk doesnt really look at it.
Hello. I added the score and was able to execute the command. Thank you very much for your help. Unrelated. I observed more TC in my untreated samples than in my 4SU treated samples. Does this suggest the experiment did not work? Thanks
@t-neumann
Like where to you see that you have more T>C conversions in your untreated sample compare to the labelled ones.
See the images: first image is treated and second is untreated 816_Amanitin_4SU_B04_S7_L004_R1_001_slamdunk_mapped_filtered_overallrates.pdf 816_Gonad_B02_S5_L002_R1_001_slamdunk_mapped_filtered_overallrates.pdf
@t-neumann
Yes that indeed looks like you have way more conversions in your untreated sample. U sure there was no sample swap or anything?