We've been using Pulsar to send jobs to our cluster on campus. Generally we send a dataset list of files over. We're wondering if there is a way to get the metadata for the files after they've been sent to the cluster. We're specifically trying to find the filepaths of the files before they were through Pulsar to the cluster.
Any guidance would be great.
Could you send the call-in information please?
On Tue, Feb 7, 2017 11:00 AM, galaxy-dev-request(a)lists.galaxyproject.org wrote:
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queries, but that aren't actually informative.Today's Topics:
1. Re: Request more details from Nikolaos Tur about pyBamTools &
pyBamParser dependency packages message (Peter Briggs)
2. GalaxyAdmins Feb online meetup (Enis Afgan)
3. Create a new datatype svg (Jochen Bick)
4. Re: Create a new datatype svg (Björn Grüning)
5. Re: Create a new datatype svg (Jochen Bick)
6. Re: Request more details from Nikolaos Tur about pyBamTools &
pyBamParser dependency packages message (Jennifer Hsieh)
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8. Re: Issue when using xsendfile with galaxy release_16.07
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I've installed a local instance of Galaxy (on Ubuntu 16.04, python 2.7.12)
and have run in to this exact problem
(posted by Nikolaos Tur
while trying to add naive_variant_caller tool.
Naive_variant_caller can't install because these two dependency packages
can't be installed.
I basically get exactly the same error message that ends with "IOError:
Could not build the egg."
Unfortunately I'm very new to both Galaxy and Python (Taking Coursera
Galaxy course at the moment) and I don't really understand the solution
Nikolaos described about modifying the setup.py to use "setuptools" instead
of "distribute". I don't even know where to find setup.py...
Can anyone help me with step-by-step details as to how to solve this
PhD Neuroscience (student)
Department of Psychiatry and Mental Health
University of Cape Town
Tell: +27 21 447 3157
Cell: +27 74 841 4761
We are going to have a GalaxyAdmins call this month! This is a wonderful
venue to get an update on what's going on in the Galaxy community as mostly
relevant to people managing Galaxy instance(s).
The talk will be held at the 'standard' GalaxyAdmins time: on Feb 16th at
Here is a short description of the topic that will be presented:
CloudLaunch is an application for launching Galaxy on the Cloud instances.
In this talk, an all-new version will be presented. The new CloudLaunch (
beta.launch.usegalaxy.org) allows multiple flavors of Galaxy to be
deployed, Docker images or applications other than Galaxy. Each application
can have its own custom user interface developed to accommodate the
specific application needs, which will be demonstrated.
The call will be held online, using an online meetup room with Adobe
Connect. The online conference room will open 15 minutes before the meetup.
The call will use Johns Hopkins' Adobe Connect server, which in turn uses
Adobe Flash. You are encouraged to connect a few minutes early to work out
any unexpected bumps.
After setting up AD/LDAP in Galaxy, we noticed that for some reason, some users are able to log in but others were not. We don’t think that it has anything to do with the set up of LDAP or AD at our institute and we’ve tried to find common threads between the users who can log in but we have not found anything interesting.
Could someone explain what exactly Galaxy looks for when signing users in with AD/LDAP? We found the source code here: ./lib/galaxy/auth/providers/ldap_ad.py but all the code seems to be functioning properly.
Here is one of the error outputs in the log when somebody tries to log in for the first time, but cannot:
galaxy.auth.providers.ldap_ad DEBUG 2017-02-01 17:16:17,954 LDAP authenticate: whoami is u:SCIEDU\chess
galaxy.auth.providers.ldap_ad DEBUG 2017-02-01 17:16:17,954 LDAP authentication successful
server ip - - [01/Feb/2017:17:16:12 -0400] "POST /galaxy/user/login?use_panels=False HTTP/1.0" 200 - “http:/galaxyurl.edu/galaxy/user/login?use_panels=False<http://galaxy/user/login?use_panels=False>" "Mozilla/5.0 (Macintosh; Intel Mac OS X 10_11_6) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/55.0.2883.95 Safari/537.36"
Exception happened during processing of request from ('127.0.0.1', 55724)
Traceback (most recent call last):
File "/localdata1/galaxy/.venv/lib/python2.7/site-packages/paste/httpserver.py", line 1085, in process_request_in_thread
File "/usr/lib64/python2.7/SocketServer.py", line 334, in finish_request
self.RequestHandlerClass(request, client_address, self)
File "/usr/lib64/python2.7/SocketServer.py", line 651, in __init__
File "/usr/lib64/python2.7/SocketServer.py", line 710, in finish
File "/usr/lib64/python2.7/socket.py", line 279, in close
File "/usr/lib64/python2.7/socket.py", line 303, in flush
error: [Errno 32] Broken pipe
Any insight would be appreciated. Thanks!
I’m trying to setup various data managers to automatically download and index reference indices. However, I can’t figure out where to change the default location where these are saved. As you can see in the attached image, the default location for the indexes is the … /tool-data/dbkey/index_name However, I would like to save them in /projects/reference_datasets which is a shared location that has a lot of space available.
Thank you all !
Dear Galaxy Community,
I am a Ph.D. student working on Plasmodium Genome. My project mainly focuses on short Amplicon sequence using Miseq platform and I have a total of 200 primers designed for targeted 200 loci on 14 chromosomes. I would like to ask you which pipeline would be better to do demultiplex 200 primers/ sample for 96 samples (output from MiSeq), quality filter, mapping reads and variant calling simultaneously. Since the majority of current pipelines (GATK and others) are designed for large reads and diploid organism like human. Any suggestion or comment highly appreciated for my data (short millions of multiplexed reads for a haploid organism)...
I'm a new user of Galaxy. I have been exploring the things and trying to
use the Docker image of Galaxy. Eventually, I am planning to run the docker
container on our local Cluster.
I was wondering if there's any way to include local tools with the
Dockerfile. For example using the Docker image of Galaxy at
https://github.com/bgruening/docker-galaxy-stable it shows how to include
the tools to the Docker image of Galaxy from the Galaxy tool shed as
RUN install-repository \
"--url https://toolshed.g2.bx.psu.edu/ -o iuc --name package_numpy_1_7"
"--url https://toolshed.g2.bx.psu.edu/ -o iuc --name
This command will pull the tools from the Galaxy tool shed and install
inside the docker container. But, is there's any similar way to include my
own local tools?
*Md. Rezaul Karim*, BSc, MSc
PhD Researcher, INSIGHT Centre for Data Analytics
National University of Ireland, Galway
IDA Business Park, Dangan, Galway, Ireland