minimum configuration example:
workdir: workspace
# can be "ECLIP10", "ECLIP6", "TAKARAV3", "SACSEQV3", "STRANDED"
libtype: ECLIP10
# TODO: if the genome index is not available, the pipeline will build it automatically
genome_index: /data/reference/genome/Arabidopsis_thaliana/hisat2_tx_3n/TAIR10.release57
reference:
contamination:
# Multiple contaminant reference files are allowed
- ref/Agrobacterium.fa.gz
genes:
# Multiple gene reference files are allowed
- ref/spikein.fa
- ref/ERCC92.fa
- ref/cress_rRNA.fa
genome:
# Only one genome is allowed
- /data/reference/genome/Arabidopsis_thaliana/TAIR10.fa
samples:
cress1:
data:
- R1: data/cress1_R1.fq.gz
R2: data/cress1_R2.fq.gz
cress2:
data:
- R1: data/cress2_R1.fq.gz
R2: data/cress2_R2.fq.gz
Warning
different from previous version (v1), a 3rd level of "data:" tag is added into "samples:" section this is a preserved behavior for future expansion
advanced configuration: please refer to docs/configuration.md
apptainer run docker://y9ch/camseq -c data.yaml -j 48
Tip
apptainer cannot detect mounted partitions by default, you need to add -B /partition_name
flag right after the run
command.
Tip
If you work on a remote server with internet access, you can compile the pipeline first
apptainer build camseq.sif docker://y9ch/camseq:v2
apptainer run camseq.sif -c data.yaml -j 48
Tip
For using the previous version of pipeline (v1), try:
apptainer run docker://y9ch/camseq:v1 -c data.yaml -j 48
System Requirements
This package has been tested on Linux operating systems. It requires the following software dependencies:
The documentation is available at https://y9c.github.io/m6A-CAMseq/
-
update in May 11, 2025
- data processing steps is now based on trichromat
- m6A site detection and filtering is now automatically and have been combined with the pipeline
-
update in May 13, 2025 (v2.1)
- the m6A calling step is also based on trichromat
- the rate limiting step from the 3n-table has been removed
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Copyright © 2023-present Chang Y