Seq is a programming language for computational genomics and bioinformatics. With a Python-compatible syntax and a host of domain-specific features and optimizations, Seq makes writing high-performance genomics software as easy as writing Python code, and achieves performance comparable to (and in many cases better than) C/C++.
Seq is able to outperform Python code by up to 160x. Seq can further beat equivalent C/C++ code by up to 2x without any manual interventions, and also natively supports parallelism out of the box. Implementation details and benchmarks are discussed in our paper.
Learn more by following the tutorial or from the cookbook.
Here is an example showcasing some of Seq's bioinformatics features, which include native sequence and k-mer types.
from bio import *
s = s'ACGTACGT' # sequence literal
print(s[2:5]) # subsequence
print(~s) # reverse complement
kmer = Kmer[8](s) # convert to k-mer
# iterate over length-3 subsequences
# with step 2
for sub in s.split(3, step=2):
print(sub[-1]) # last base
# iterate over 2-mers with step 1
for kmer in sub.kmers(step=1, k=2):
print(~kmer) # '~' also works on k-mersPlease check docs.seq-lang.org for in-depth documentation.
If you use Seq in your research, please cite:
Ariya Shajii, Ibrahim Numanagić, Riyadh Baghdadi, Bonnie Berger, and Saman Amarasinghe. 2019. Seq: a high-performance language for bioinformatics. Proc. ACM Program. Lang. 3, OOPSLA, Article 125 (October 2019), 29 pages. DOI: https://doi.org/10.1145/3360551
BibTeX:
@article{Shajii:2019:SHL:3366395.3360551,
author = {Shajii, Ariya and Numanagi\'{c}, Ibrahim and Baghdadi, Riyadh and Berger, Bonnie and Amarasinghe, Saman},
title = {Seq: A High-performance Language for Bioinformatics},
journal = {Proc. ACM Program. Lang.},
issue_date = {October 2019},
volume = {3},
number = {OOPSLA},
month = oct,
year = {2019},
issn = {2475-1421},
pages = {125:1--125:29},
articleno = {125},
numpages = {29},
url = {http://doi.acm.org/10.1145/3360551},
doi = {10.1145/3360551},
acmid = {3360551},
publisher = {ACM},
address = {New York, NY, USA},
keywords = {Python, bioinformatics, computational biology, domain-specific language, optimization, programming language},
}