himal_scripts
is a collection of custom scripts for processing MDU data.
To use these scripts, you need to clone this repository and make the scripts executable:
git clone https://github.com/MDU-PHL/himal_scripts.git
cd himal_scripts
chmod +x *.sh
This script checks the MLST outputs for a sample with genomes assembled using spades
, shovill
and skesa
. It takes two arguments: the run ID
and the sample ID
.
Example:
conda activate /home/khhor/conda/envs/mlst/
./run_mlst <runid> <sampleid>
This will output the MLST scheme using genomes from each assembly method.
This script runs hicap on a set of samples. It takes one argument: a file containing the sample IDs, one per line.
Before running this script, you need to create a new folder for the test run and copy the script to that folder. You also need to activate the conda environment for hicap:
mkdir 231205-test
cd 231205-test
cp /home/himals/3_resources/github-repos/himal_scripts/test-hicap-run.sh test-hicap-run.sh
conda activate /home/himals/.conda/envs/hicap_dev
Then, you need to create a file called sample_ids
and paste the sample IDs in the file:
nano sample_ids
Finally, you can run the script with the following command:
./test-hicap-run.sh sample_ids
This will run hicap on each sample and generate a folder called hicap_ssummary
files in the current directory, which contains the hicap results for each sample.
This script runs in sillico PCR on a fasta file using seqkit amplicon
. It takes two arguments: a file containing the primer information (primer_info
) and a file containing sample_IDs (sample_ids
).
primer_info
file should contain the following information as a tab separated file, example:
Serotype Forward primer Reverse primer
Hia GGTCTGCGGTGTCCTGTGT CCGGTCATCTTTTATGCTCCAA
Hib GGGGGGGGGGGGGGGGGGG CCCCCCCCCCCCCCCCCCCC
sample_IDs
file should contain the sample IDs, one per line, example:
2015-11111
2015-11112
2015-11113
Usage:
./seqkit-pcr.sh primer_info sample_ids
This will output the PCR results for each sample_IDs tested for a different serotype in the file detection_results.csv
and detailed PCR results for each sample in the folder detailed_results
.
If you want to contribute to this project, please follow these steps:
- Fork this repository and create a new branch for your feature or bug fix.
- Make your changes and commit them with a clear and descriptive message.
- Push your branch to your fork and open a pull request to the main branch.
- Wait for a review and feedback from the maintainer.
This project is licensed under the MIT License. See the LICENSE file for details.