A standardized R-loop-mapping pipeline
Project description
RLPipes
RLPipes is an upstream workflow for R-loop-mapping data.
The primary outputs of the pipeline are:
- Coverage (.bw) tracks
- Peaks (.broadpeak) files
- Alignment (.bam) files
- RLSeq report (.html and .rda) files
Following RLPipes, the RLSeq R package can be used for more fine-grained downstream analysis.
Install
The preferred installation method is mamba or conda (slower):
mamba create -n rlpipes -c bioconda -c conda-forge rlpipes
conda activate rlpipes
Using pip
RLPipes can also be installed with pip. However, system dependencies will
still need to be installed. To accomplish this, do the following:
git clone https://github.com/Bishop-Laboratory/RLPipes.git
cd RLPipes/
conda install -c conda-forge mamba -y
mamba env create -f rlpipes.yml --force
conda activate rlpipes
python -m pip install -e .
Basic Usage
To run RLPipes, you will need a samples.csv file that describes your samples.
Here is an example file provided for testing purposes:
| experiment | control |
|---|---|
| SRX113814 | |
| SRX1025890 | SRX1025893 |
| SRX1025899 |
The basic usage of RSeq follows a three-step process: build, check , and run.
Build
RLPipes build generates a config.json file that controls the underlying snakemake workflow.
RLPipes build -m DRIP rlpipes_out/ tests/test_data/samples.csv
Output:
Success! RSeq has been initialized at the specified directory: rlpipes_out/
Run 'RLPipes check rlpipes_out/' to verify the configuration.
Check
Verifies that the run will succeed and generates a plot of the workflow jobs.
RLPipes check rlpipes_out/
Output:
Success! The DAG has been generated successfully. You can view it here: rlpipes_out/dag.png
Run 'RLPipes run rlpipes_out/' to execute the workflow.
Run
Executes the workflow rules.
RLPipes run rlpipes_out/
If multiple cores are available, they can be specified using the --threads/-t option.
RLPipes run -t 30 rlpipes_out/
Usage Reference
Top-level usage:
Usage: RLPipes [OPTIONS] COMMAND [ARGS]...
RSeq: An R-loop mapping pipeline with built-in QC.
Options:
--version Show the version and exit.
--help Show this message and exit.
Commands:
build Configure an RSeq workflow.
check Validate an RSeq workflow.
run Execute an RSeq workflow.
Build
Usage: RLPipes build [OPTIONS] RUN_DIR SAMPLES
Configure an RLPipes workflow.
RUN_DIR: Directory for RLPipes Execution. Will be created if it does not
exist.
SAMPLES: A CSV file with at least one column "experiment" that provides the
path to either local fastq files, bam files, or public sample accessions
(SRX or GSM). Input controls should be in the "control" column.
If providing paired-end fastq files, enter: "exp_1.fastq~exp_2.fastq".
Columns may also include "genome" and "mode" columns. These will override
the -g, -m, and -n options.
"genome" (-g/--genome) is not required if providing public data accessions.
Example #1: "RLPipes build -m DRIP outdir/ samples.csv"
samples.csv:
experiment
SRX113812
SRX113813
Example #2: "RLPipes build outdir/ samples.csv"
samples.csv:
experiment, control, genome, mode
qDRIP_siGL3_1.fq~qDRIP_siGL3_2.fq, , hg38, qDRIP
DRIPc_3T3.fq, Input_3T3.fq, mm10, DRIPc
Options:
-m, --mode TEXT The type of sequencing (e.g., "DRIP"). The available
options are currently: DRIP, DRIPc, qDRIP, sDRIP, ssDRIP,
R-ChIP, RR-ChIP, RDIP, S1-DRIP, DRIVE, RNH-CnR, and MapR
-g, --genome TEXT UCSC genome for samples (e.g., 'hg38'). Not required if
providing public data accessions.
-n, --name TEXT Sample names for use in output report. By default,
inferred from inputs.
--help Show this message and exit.
Check
Usage: RLPipes check [OPTIONS] RUN_DIR
Validate an RLPipes workflow.
RUN_DIR: Directory configured with `RLPipes build` and ready for checking
and execution.
Options:
-s, --smargs TEXT Dict of arguments passed to the snakemake python API.
Default: "{'use_conda': True}". Read the snakemake
API reference for the full list of options.
-t, --threads INTEGER Number of threads to use. Default: 1
--bwamem2 Align with BWA-MEM2 instead of BWA. BWA MEM2 Needs >
70GB RAM avaialble to build index, but shows > 3x
speed increase. Default: False.
--macs2 Call peaks using macs2 instead of macs2
-G, --groupby TEXT Column(s) which identify biologically-meaningful
grouping(s) of samples (i.e., conditions). Can be
any column name from the `samples` CSV file. If using
public data accessions, it may also include "study".
NOTE: If --groupby is set and there R-loop-mapping
and expression samples within groups, expression-
matched analysis will be run. This can be disabled
with the --noexp flag.
Example #1: "RSeqCLI build outdir/ samples.csv
--groupcols tissue"
samples.csv:
experiment, mode, tissue
GSM1720615, DRIP, NT2
GSM1720616, DRIP, NT2
GSM1720619, DRIP, K562
Example #2: "RSeqCLI build outdir/ samples.csv
--groupby tissue"
samples.csv:
experiment, mode, tissue
GSM1720615, DRIP, NT2
GSM1720616, DRIP, NT2
GSM1720613, DRIPc, NT2
GSM1720614, DRIPc, NT2
GSM1720622, RNA-seq, NT2
GSM1720623, RNA-seq, NT2
--noexp If set, no expression-matched analysis will be
performed.
--noreport If set, RLSeq reports will not be generated.
--debug Run pipeline on subsampled number of reads (for
testing).
--tsv Obtain config from config.tsv file instead of
config.json.
--noaws If set, prefetch from SRA tools will be used to
download any public SRA data instead of AWS S3.
--help Show this message and exit.
Run
Usage: RLPipes run [OPTIONS] RUN_DIR
Execute an RLPipes workflow.
RUN_DIR: Directory configured with `RLPipes build` and ready for checking
and execution.
Options:
-s, --smargs TEXT Dict of arguments passed to the snakemake python API.
Default: "{'use_conda': True}". Read the snakemake
API reference for the full list of options.
-t, --threads INTEGER Number of threads to use. Default: 1
--bwamem2 Align with BWA-MEM2 instead of BWA. BWA MEM2 Needs >
70GB RAM avaialble to build index, but shows > 3x
speed increase. Default: False.
--macs2 Call peaks using macs2 instead of macs2
-G, --groupby TEXT Column(s) which identify biologically-meaningful
grouping(s) of samples (i.e., conditions). Can be
any column name from the `samples` CSV file. If using
public data accessions, it may also include "study".
NOTE: If --groupby is set and there R-loop-mapping
and expression samples within groups, expression-
matched analysis will be run. This can be disabled
with the --noexp flag.
Example #1: "RSeqCLI build outdir/ samples.csv
--groupcols tissue"
samples.csv:
experiment, mode, tissue
GSM1720615, DRIP, NT2
GSM1720616, DRIP, NT2
GSM1720619, DRIP, K562
Example #2: "RSeqCLI build outdir/ samples.csv
--groupby tissue"
samples.csv:
experiment, mode, tissue
GSM1720615, DRIP, NT2
GSM1720616, DRIP, NT2
GSM1720613, DRIPc, NT2
GSM1720614, DRIPc, NT2
GSM1720622, RNA-seq, NT2
GSM1720623, RNA-seq, NT2
--noexp If set, no expression-matched analysis will be
performed.
--noreport If set, RLSeq reports will not be generated.
--debug Run pipeline on subsampled number of reads (for
testing).
--tsv Obtain config from config.tsv file instead of
config.json.
--help Show this message and exit.
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