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github_document |
Repo of Collaboration with Barbieri. The pipeline use cellranger v7
to align the fastq.
Project uses {targets}
and {renv}
and {here}
.
data/
contains the reference and a user provided csv mapping that indicates the location of the samples, as well
as the results of alignment.
mapping_folders.csv
andmapping_folders_2.csv
are used in one of the targets to map folders containing fastqs to specific sample names.batch_1_2_aggr.csv
is used by the target that runscellranger aggr
reference
andrefdata_*
contains the references used for alignment.- **
alignment_results/
**contains the outputs of cellranger alignment. Each folder is the alignment of one sample. The samples are then aggregated together in thealignment_results/batch_1_2
folder.
code/
functions called by _targets.R
in here::here("code", "targets_functions"))
The pipeline uses {targets}
(https://books.ropensci.org/targets/) and is setup to run in parallel on SLURM (with {future.batchtools}
).
The files batchtools.slurm.tmpl
and .batchtools.conf.R
are configuration files used by the API {future.batchtools}
to
communicate with SLURM.
Insert path to your home directory in .batchtools.conf.R
and copy batchtools.slurm.tmpl
to you home directory.
Resources to deploy for each target are specified in the file _targets_resources.conf.R
that is sourced in the
main _targets.R
file.
Use targets::tar_make_future(workers = 10)
from inside srun
interactive session or run sbatch start_targets.sh
to initiate the pipeline. The job master
will control the execution of the other jobs.
SLURM Logs are created in log/
(be sure to have a folder with that name in the current directory).
A reproducible R environment is maintained using {renv}
Initialize and install packages with:
renv::restore()
Run the pipeline.
targets::tar_make()
Check manifest with targets::tar_manifest()
and Load targets with targets::tar_load("name_of_target)