A script to process fastqs from ASAP-seq for downstream processing with kite (kallisto | bustools).
The options are designed to mirror that of CellRanger/CellRanger-ATAC for convenience in processing.
There are two scripts in this repository. First, asap_to_kite_vX.py (where X is an integer) represents the tool most commonly used for the simple reformatting. This will work most of the time.
In rare cases, you may have stained with both TSA and TSB antibodies. In this case, we have the asap_to_kite_A_B.py to separate out the two using the different PCR handles. For this to work, we do require the pre-identification of the valid barcodes for both TSA and TSB; hence, additional parameters in the -a and -b flags.
The most basic use case is when we have one library sequenced one. From the demultiplexing, we should see files that look like this:
test/data1/test1_S1_L001_R1_001.fastq.gz
test/data1/test1_S1_L001_R2_001.fastq.gz
test/data1/test1_S1_L001_R3_001.fastq.gz
test/data1/test1_S1_L002_R1_001.fastq.gz
test/data1/test1_S1_L002_R2_001.fastq.gz
test/data1/test1_S1_L002_R3_001.fastq.gz
test/data1/test1_S1_L003_R1_001.fastq.gz
test/data1/test1_S1_L003_R2_001.fastq.gz
test/data1/test1_S1_L003_R3_001.fastq.gz
test/data1/test1_S1_L004_R1_001.fastq.gz
test/data1/test1_S1_L004_R2_001.fastq.gz
test/data1/test1_S1_L004_R3_001.fastq.gz
Here, the sequencing run is in the folder test/data1 and we are interested in the test1 sample.
We can process these fastqs:
python asap_to_kite_v1.py -f test/data1 -s test1 -o one_one
Here, the -s specifies the sample name; -f specifies the fastq folder; -o specifies the output naming convention.
If multiple sequencing rounds are performed, we can supply all sequencing libraries as a comma-separated list:
python asap_to_kite_v1.py -f test/data1,test/data2 -s test1 -o one_many
Suppose that the sequencing library is named two different ways over the two sequencing runs. We can stack the comma-separated nature of the sample names and the sequencing runs to synthesize the libraries
python asap_to_kite_v1.py -f test/data1,test/data2 -s test1,test2 -o many_many
Finally, just to showcase that we can write these files out to a different path:
python asap_to_kite_v1.py -f test/data1,test/data2 -s test1,test2 -o test/many_many
This code works for one biological sample at a time. If multiple samples are supplied in the command line execution, then they will be merged (under the assumption that they were called different things). Execute the code sequentially for each sample in the event of multiple biological samples.
python asap_to_kite_v1.py --help
yields
Usage: asap_to_kite_v1.py [options] [inputs] Script to reformat raw sequencing
data from CellRanger-ATAC demultiplexing to a format
compatible with kite (kallisto|bustools)
Options:
-h, --help show this help message and exit
-f FASTQS, --fastqs=FASTQS
Path of folder created by mkfastq or bcl2fastq; can be
comma separated that will be collapsed into one
output.
-s SAMPLE, --sample=SAMPLE
Prefix of the filenames of FASTQs to select; can be
comma separated that will be collapsed into one output
-o ID, --id=ID A unique run id, used to name output.
-c CORES, --cores=CORES
Number of cores for parallel processing. Default = 4.
-n NREADS, --nreads=NREADS
Maximum number of reads to process in one iteration.
Decrease this if in a low memory environment (e.g.
laptop). Default = 10,000,000.
-r, --no-rc-R2 By default, the reverse complement of R2 (barcode) is
performed (when sequencing with, for example, the
NextSeq). Throw this flag to keep R2 as is-- no
reverse complement (rc).
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