bowtie2 | A fast and sensitive gapped read aligner | Genomics library

Hello I just want to apply a loop to a set of files, but instead of doing it to all my files I want to make the loop just only to certain files in a directory

Here is the command that I use, is a bowtie2 based alignment of genomic sequences:

I have a pipeline which uses a global singularity image and rule-based conda wrappers.

However, some of the tools don't have wrappers (i.e. htslib's bgzip and tabix).

Now I need to learn how to run jobs in containers.

In the official documentation link it says:

"Allowed image urls entail everything supported by singularity (e.g., shub:// and docker://)."

Now I've tried the following image from singularity hub but I get an error:

I'm trying to build database bacteria genre using all the sequences published to calculate the coverage of my reads against this database using bowtie2 for mapping, for that, I merge all the genomes sequences I downloaded from ncbi in one fasta_library ( i merge 74 files in on fasta file ), the problem is that in this fasta file (the library I created ) I have a lot of duplicated sequences, and that affected the coverage in a big way, so I'm asking if there's any way to eliminate duplication I have in my Library_File, or if there's any way to merge the sequences without having the duplication, or also if there's any other way to calculate the coverage of my reads against reference sequences

I hope I'm clear enough, please tell me if there's anything not clear.

I'm running the following command using subprocess.check_call

['/home/user/anaconda3/envs/hum2/bin/bowtie2-build', '-f', '/media/user/extra/tmp/subhm/sub_humann2_temp/sub_custom_chocophlan_database.ffn', '/media/user/extra/tmp/subhm/sub_humann2_temp/sub_bowtie2_index', ' --threads 8']

But for some reason, it ignores the --threads argument and runs on one thread only. I've checked outside of python with the same command that the threads are launched. This only happens when calling from subprocess, any idea on how to fix this?

thanks

I know this is a common error and I already checked other posts but it didn't resolved my issue. I would like to use the name of the database I use for SortMeRNA rule (rRNAdb=config["rRNA_database"]) the same way I use version=config["genome_version"]. But obviously, I can't.

I have files with names like:

I am running a snakemake pipeline on a slurm HPC. Occasionally, jobs will fail due to exceeded wall time or memory. Such failed jobs do not create log files, or their log files are deleted as part of snakemakes automatic removal of files associated with failed jobs. It would be convenient to get the logging information for failed jobs so that I could more easily understand why the job failed.

I currently have logs params sat for each job, and the cluster.json file then calls those logs for each job specifically. A general rule, it's cluster.json call and my snakemake call are shown below.

I have written some code in a bash shell (so I can submit it to my university's supercomputer) to edit out contaminant sequences from a batch of DNA extracts I have. Essentially what this code does is take the sequences from the negative extraction blank I did (A1-BLANK) and subtract it from all of the other samples.

I have figured out how to get this to work with individual samples, but I'm attempting to write a for loop so that the little chunks of code will reiterate themselves for each sample, with the outcome of this file being a .sam file with a unique name for each sample where both the forward and reverse reads for the sample are merged and edited for contamination.I have checked stack overflow extensively for help with this specific problem, but haven't been able to apply related answered questions to my code.

Here's an example of part what I'm trying to do for an individual sample, named F10-61C-3-V4_S78_L001_R1_001.fastq:

I am running a very common bioinformatic tool/command bowtie2-build. It can use multi-threads on a single node (not a MPI type job). I have the following sbatch script (basically):