PowTNRka is a CRISPResso2-like software that can align sequencing reads against repetitive sequences. Its name comes from the Polish word "powtórka", meaning "repeat".
PowTNRka is written in Python 3.8 with Cython. A full list of package
dependencies can be found in requirements.txt.
PowTNRka has been tested on MacOS and Linux, though it should also work with Windows.
To install powTNRka in a Python virtual environment, run:
git clone https://github.com/alvin-hsu/powtnrka
cd powtnrka
python -m venv ./venv
. venv/bin/activate
pip install -r requirements.txt
Installation should typically take 10 to 15 minutes.
To run powTNRka, you need to provide a "reference" template. This can be any nucleotide sequence in IUPAC nomenclature. To denote repeats, simply use a template with the repeated sequence in parentheses. If you are interested in comparisons against a specific repeat sequence (i.e., for base editing), then a specific sequence can also be specified. For example, for base editing in the FXN gene, the reference template looks like this:
>Reference
ACTAACCTGGCCAACATGGTGAAACCCAGTATCTACTAAAAAATACAAAAAAAAAAAAAAAA(GAA|GRR)AATAAAG
AAAAGTTAGCCGGGCGTGGTGTCGCGCGCCTGTAATCCCAGCTACTCCAGAGGCTGCGGCAGGAGAATCGCTTGAGCC
CGGGAGGCAGAGGTTGCATTAA
Here, the reference looks for GRR repeats, which encapsulates all possible
alleles that can result from base editing of a GAA repeat. Here, we've also
added (GAA) as a specific allele so that calculating the number of edited
repeats in a genotype can be done by simply subtracting the number of repeats
aligned to GRR from those aligned to GAA.
To run powTNRka, if $R1_FASTQ is the sequencing output FASTQ file and
$OUT_DIR is the output directory, run:
main.py $R1_FASTQ $OUT_DIR -a $REF # Specify template in command
or
main.py $R1_FASTQ $OUT_DIR -af $REF_FASTA # Specify template in FASTA
PowTNRka outputs three main files for each run: Reference_DETAILED.xlsx is
an Excel file with a detailed breakdown (by segment) for every read in tabs.
Reference_FULL_alignments.csv is a CSV file with alignments for each read.
Reference_SUMMARY.xlsx is an Excel file with a summary of the run outputs.
Here is a screenshot of a summary file:
The expected runtime on a file with ~50,000 reads is 10 minutes on an average desktop computer.