google/deepconsensus
DeepConsensus uses gap-aware sequence transformers to correct errors in Pacific Biosciences (PacBio) Circular Consensus Sequencing (CCS) data.
DeepConsensus helps genetic researchers and bioinformaticians improve the accuracy of DNA sequencing data from Pacific Biosciences (PacBio) machines. It takes raw 'subreads' generated by a PacBio sequencer and processes them to produce highly accurate, 'corrected reads' in FASTQ format. This allows for more reliable downstream analyses like variant calling and genome assembly, leading to a higher yield of useful sequencing data.
256 stars. No commits in the last 6 months. Available on PyPI.
Use this if you are working with PacBio sequencing data and need to enhance the accuracy of your reads for more reliable genetic analysis or genome assembly.
Not ideal if your `ccs` settings filter out reads with a predicted quality below 20 by default, as DeepConsensus works best with unfiltered raw subreads.
Stars
256
Forks
38
Language
Python
License
BSD-3-Clause
Category
Last pushed
Mar 11, 2025
Commits (30d)
0
Dependencies
7
Get this data via API
curl "https://pt-edge.onrender.com/api/v1/quality/transformers/google/deepconsensus"
Open to everyone — 100 requests/day, no key needed. Get a free key for 1,000/day.
Related models
ThilinaRajapakse/simpletransformers
Transformers for Information Retrieval, Text Classification, NER, QA, Language Modelling,...
jsksxs360/How-to-use-Transformers
Transformers 库快速入门教程
Denis2054/Transformers-for-NLP-2nd-Edition
Transformer models from BERT to GPT-4, environments from Hugging Face to OpenAI. Fine-tuning,...
abhimishra91/transformers-tutorials
Github repo with tutorials to fine tune transformers for diff NLP tasks
Nicolepcx/transformers-the-definitive-guide
This is the official repository for the book Transformers - The Definitive Guide