This page is just meant for general questions that I notice are asked with some frequency. If you feel like something is missing from here and you'd like to see it included, feel free to ask it by raising an issue on GitHub.
If you supply all reads to the recover
command then Aviary will perform assembly first and then perform MAG recovery. You can perform assembly first by using the assemble
command and then using the output assembly file as the input to the recover
command. However, it is much simpler to let aviary handle this process for you.
All of the error messages are stored in the logs/
folder. The error messages are stored in the logs/
folder with the name of the file corresponding the name of the rule that they originate from. If you had an error occur in the qc_short_reads
rule then consult the logs/qc_short_reads.log
file for the error message.
Yes! Consult the examples page for more information.
Yes! Aviary supports the use of GPUs for the assembly process. If the GPU is on a local machine, you must first install the cuda
package into your conda environment. Then, programs that use GPUs should automatically detect its presence.
If you are using a cluster, you can supply the --request-gpu
flag and Aviary will attempt to place rules that use GPUs on to a machine that has GPUs available.
This error is almost always caused by the user running out of storage in their /tmp
folder when coverm
performs the mapping process. To fix this, you can either increase the amount of storage available to the /tmp
folder or you can change the location of the temporary folder by setting the TMPDIR
environment variable to a folder with more storage. Aviary also allows the user to specify the location of the temporary folder by using the --tmpdir
parameter.
Aviary supports the removal of host contamination during the assembly process via the -r
, --reference-filter
parameter. This flag can take one or more compressed or non-compressed fasta files. Aviary will then compare the reads to these references and remove any reads that map to them.
The most likely solution to this is that you are running out of memory. SPAdes is a memory intensive program and will exit unexpectedly if it reaches the maximum memory limit of your machine or supplied by aviary.
To increase the amount of memory available to SPAdes, you can either increase the amount of memory available to the entire pipeline by using the -m
parameter.
A known issue with using snakemake + pysam + qsub results in the a break in the pipeline. The issue arises because pysam
does not activate correctly when using qsub by default. To fix this you just need to add the -V
parameter to your qsub
command.
It is probably best to just let Aviary handle the downloading of your databases via the --download
parameter. But, if you
would like to set them up yourself, please read ahead
For the GTDB:
db/
folder inside of that download.The optional databases are as follows:
Aviary will ask for the paths to these database files if they don't exist, otherwise you can place these lines into
the activate.d/aviary.sh
or .bashrc
files changing the specific paths:
export GTDBTK_DATA_PATH=/path/to/gtdb/gtdb_release207/db/ # https://gtdb.ecogenomic.org/downloads
export EGGNOG_DATA_DIR=/path/to/eggnog-mapper/2.1.7/ # https://github.com/eggnogdb/eggnog-mapper/wiki/eggNOG-mapper-v2.1.5-to-v2.1.7#setup
export SINGLEM_METAPACKAGE_PATH=/path/to/singlem_metapackage.smpkg/
export CHECKM2DB=/path/to/checkm2db/
export CONDA_ENV_PATH=/path/to/conda/envs/
Put all your birds in one place.
I made it (among other bird based + CoverM logos) using GIMP and based the idea off of this tutorial. They are very easy to make so just follow that video if you feel like making something similar.
You sound like my supervisor.
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