How to merge identified hqSNVs to construct a multiple sequence alignment?

[sekhwal]

Hi, I am using the SNVphy pipeline. In the step 4 in its workflow, it has mentioned "Merging the identified hqSNVs to construct a multiple sequence alignment." Please let me know which software or script are used for merging the identified hqSNVs.

Thank you,

[apetkau]

Hello @sekhwal, are you running this via Galaxy? This should all be handled by the Galaxy workflow https://snvphyl.readthedocs.io/en/latest/user/usage/#running-the-workflow

[sekhwal]

Hi Petkau, Thank you for your reply. I am using Galaxy with the login credentials : admin@galaxy.org and admin. Please let me know, the analysis of my 70 samples would be faster using the Galaxy server or using the command line.

[sekhwal]

I think, I am getting some issue installing Galaxy. Once I am uploading the data, it shows the following error. It shows the docker space is full but not sure how to figure out. Please let me know if any suggestion.

Also, once I run the following command, it shows "Bind for 0.0.0.0:48888 failed: port is already allocated."

docker run -d -p 48888:80 -v /home/user/galaxy_storage/:/export/ phacnml/snvphyl-galaxy-1.0.1

[apetkau]

Hello @sekhwal ,

Just to make sure, you don't have a separate Galaxy server running someplace outside of your local computer am I correct? If that's the case, then the command-line (or Galaxy) would both be equivalent since the command-line tool simply runs Galaxy as a Docker container.

Also, once I run the following command, it shows "Bind for 0.0.0.0:48888 failed: port is already allocated."

You likely still have a previous version of Galaxy/Docker running. You can check for it using docker ps. And kill it using docker kill [identifier] (or docker rm -f -v [identifier] to clean up after it). Please see https://github.com/bgruening/docker-galaxy-stable for more information on Galaxy and Docker.

Unfortunately I don't think there is any way to speed things up if you are running everything on your local computer. Processing 70 genomes is going to take a lot of resources and time. You could try other software (like snippy: https://github.com/tseemann/snippy) too, but even still, the main issue is the amount of data you are trying to process.

[sekhwal]

Thank you for the information. However, my major concern is that when I upload the data using Galaxy it fills up my computer space very quickly and I am not getting how to delete previously uploaded and generated data using Galaxy docker and which location the uploading data are stored using the galaxy docker? Sorry, I am not very familiar with docker. if you could give quick guidance on how to delete the previous data at Galaxy docker and get the space back and on which location data is stored, it would be much appreciated.

Manoj

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On Mon, Jan 31, 2022 at 4:28 PM Aaron Petkau @.***> wrote:

Hello @sekhwal https://github.com/sekhwal ,

Just to make sure, you don't have a separate Galaxy server running someplace outside of your local computer am I correct? If that's the case, then the command-line (or Galaxy) would both be equivalent since the command-line tool simply runs Galaxy as a Docker container.

Also, once I run the following command, it shows "Bind for 0.0.0.0:48888 failed: port is already allocated."

You likely still have a previous version of Galaxy/Docker running. You can check for it using docker ps. And kill it using docker kill [identifier] (or docker rm -v [identifier] to clean up after it). Please see https://github.com/bgruening/docker-galaxy-stable for more information on Galaxy and Docker.

Unfortunately I don't think there is any way to speed things up if you are running everything on your local computer. Processing 70 genomes is going to take a lot of resources and time. You could try other software (like snippy: https://github.com/tseemann/snippy) too, but even still, the main issue is the amount of data you are trying to process.

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