SARS-Cov-2 Recombinant Finder for fasta sequences

Sc2rf - SARS-Cov-2 Recombinant Finder

Pronounced: Scarf

What's this?

Sc2rf can search genome sequences of SARS-CoV-2 for potential recombinants - new virus lineages that have (partial) genes from more than one parent lineage.

Is it already usable?

This is a very young project, started on March 5th, 2022. As such, proceed with care. Results may be wrong or misleading, and with every update, anything can still change a lot.

Anyway, I'm happy that scientists are already seeing benefits from Sc2rf and using it to prepare lineage proposals for cov-lineages/pango-designation.

Though I already have a lot of ideas and plans for Sc2rf (see at the bottom of this document), I'm very open for suggestions and feature requests. Please write an issue, start a discussion or get in touch via mail or twitter!

Example output

Requirements and Installation

You need at least Python 3.6 and you need to install the requirements first. You might use something like python3 -m pip install -r requirements.txt to do that. There's a setup.py which you should probably ignore, since it's work in progress and does not work as intented yet.

Also, you need a terminal which supports ANSI control sequences to display colored text. On Linux, MacOS, etc. it should probably work.

On Windows, color support is tricky. On a recent version of Windows 10, it should work, but if it doesn't, install Windows Terminal from GitHub or Microsoft Store and run it from there.

Basic Usage

Start with a .fasta file with one or more sequences which might contain recombinants. Your sequences have to be aligned to the reference.fasta. If they are not, you will get an error message like:

Sequence hCoV-19/Phantasialand/EFWEFWD not properly aligned, length is 29718 instead of 29903.

(For historical reasons, I always used Nextclade to get aligned sequences, but you might also use Nextalign or any other tool. Installing them is easy on Linux or MacOS, but not on Windows. You can also use a web-based tool like MAFFT.)

Then call:

sc2rf.py <your_filename.fasta>

If you just need some fasta files for testing, you can search the pango-lineage proposals for recombinant issues with fasta-files, or take some files from my shared-sequences repository, which might not contain any actual recombinants, but hundreds of sequences that look like they were!

No output / some sequences not shown

By default, a lot filters are active to show only the likely recombinants, so that you can input 10000s of sequences and just get output for the interesting ones. If you want, you can disable all filters like that, which is only recommended for small input files with less than 100 sequences:

sc2rf.py --parents 1-35 --breakpoints 0-100 \
--unique 1 --max-ambiguous 10000 <your_filename.fasta>

or even

sc2rf.py --parents 1-35 --breakpoints 0-100 \
--unique 1 --max-ambiguous 10000 --force-all-parents \
--clades all <your_filename.fasta>

The meaning of these parameters is described below.

Advanced Usage

You can execute sc2rf.py -h to get excactly this help message:

usage: sc2rf.py [-h] [--primers [PRIMER ...]]
                [--primer-intervals [INTERVAL ...]]
                [--parents INTERVAL] [--breakpoints INTERVAL]
                [--clades [CLADES ...]] [--unique NUM]
                [--max-intermission-length NUM]
                [--max-intermission-count NUM]
                [--max-name-length NUM] [--max-ambiguous NUM]
                [--force-all-parents]
                [--select-sequences INTERVAL]
                [--enable-deletions] [--show-private-mutations]
                [--rebuild-examples] [--mutation-threshold NUM]
                [--add-spaces [NUM]] [--sort-by-id [NUM]]
                [--verbose] [--ansi] [--hide-progress]
                [--csvfile CSVFILE]
                [input ...]

Analyse SARS-CoV-2 sequences for potential, unknown recombinant
variants.

positional arguments:
  input                 input sequence(s) to test, as aligned
                        .fasta file(s) (default: None)

optional arguments:
  -h, --help            show this help message and exit

  --primers [PRIMER ...]
                        Filenames of primer set(s) to visualize.
                        The .bed formats for ARTIC and EasySeq
                        are recognized and supported. (default:
                        None)

  --primer-intervals [INTERVAL ...]
                        Coordinate intervals in which to
                        visualize primers. (default: None)

  --parents INTERVAL, -p INTERVAL
                        Allowed number of potential parents of a
                        recombinant. (default: 2-4)

  --breakpoints INTERVAL, -b INTERVAL
                        Allowed number of breakpoints in a
                        recombinant. (default: 1-4)

  --clades [CLADES ...], -c [CLADES ...]
                        List of variants which are considered as
                        potential parents. Use Nextstrain clades
                        (like "21B"), or Pango Lineages (like
                        "B.1.617.1") or both. Also accepts "all".
                        (default: ['20I', '20H', '20J', '21I',
                        '21J', 'BA.1', 'BA.2', 'BA.3'])

  --unique NUM, -u NUM  Minimum of substitutions in a sample
                        which are unique to a potential parent
                        clade, so that the clade will be
                        considered. (default: 2)

  --max-intermission-length NUM, -l NUM
                        The maximum length of an intermission in
                        consecutive substitutions. Intermissions
                        are stretches to be ignored when counting
                        breakpoints. (default: 2)

  --max-intermission-count NUM, -i NUM
                        The maximum number of intermissions which
                        will be ignored. Surplus intermissions
                        count towards the number of breakpoints.
                        (default: 8)

  --max-name-length NUM, -n NUM
                        Only show up to NUM characters of sample
                        names. (default: 30)

  --max-ambiguous NUM, -a NUM
                        Maximum number of ambiguous nucs in a
                        sample before it gets ignored. (default:
                        50)

  --force-all-parents, -f
                        Force to consider all clades as potential
                        parents for all sequences. Only useful
                        for debugging.

  --select-sequences INTERVAL, -s INTERVAL
                        Use only a specific range of input
                        sequences. DOES NOT YET WORK WITH
                        MULTIPLE INPUT FILES. (default: 0-999999)

  --enable-deletions, -d
                        Include deletions in lineage comparision.

  --show-private-mutations
                        Display mutations which are not in any of
                        the potential parental clades.

  --rebuild-examples, -r
                        Rebuild the mutations in examples by
                        querying cov-spectrum.org.

  --mutation-threshold NUM, -t NUM
                        Consider mutations with a prevalence of
                        at least NUM as mandatory for a clade
                        (range 0.05 - 1.0, default: 0.75).

  --add-spaces [NUM]    Add spaces between every N colums, which
                        makes it easier to keep your eye at a
                        fixed place. (default without flag: 0,
                        default with flag: 5)

  --sort-by-id [NUM]    Sort the input sequences by the ID. If
                        you provide NUM, only the first NUM
                        characters are considered. Useful if this
                        correlates with meaning full meta
                        information, e.g. the sequencing lab.
                        (default without flag: 0, default with
                        flag: 999)

  --verbose, -v         Print some more information, mostly
                        useful for debugging.

  --ansi                Use only ASCII characters to be
                        compatible with ansilove.

  --hide-progress       Don't show progress bars during long
                        task.

  --csvfile CSVFILE     Path to write results in CSV format.
                        (default: None)

An Interval can be a single number ("3"), a closed interval
("2-5" ) or an open one ("4-" or "-7"). The limits are inclusive.
Only positive numbers are supported.

Interpreting the output

To be written...

There already is a short Twitter thread which explains the basics.

Source material attribution

virus_properties.json contains data from LAPIS / cov-spectrum which uses data from NCBI GenBank, prepared and hosted by Nextstrain, see blog post.
reference.fasta is taken from Nextstrain's nextclade_data, see NCBI for attribution.
mapping.csv is a modified version of the table on the covariants homepage by Nextstrain.
Example output / screenshot based on Sequences published by the German Robert-Koch-Institut.
Primers:
- ARTIC primers CC-BY-4.0 by the ARTICnetwork project
- ~~EasySeq primers by Coolen, J. P., Wolters, F., Tostmann, A., van Groningen, L. F., Bleeker-Rovers, C. P., Tan, E. C., ... & Melchers, W. J.~~ Removed until I understand the format if the .bed file. There will be an issue soon.
- midnight primers CC-BY-4.0 by Silander, Olin K, Massey University

The initial version of this program was written in cooperation with @flauschzelle.

SARS-Cov-2 Recombinant Finder for fasta sequences

Related tags

Overview

Sc2rf - SARS-Cov-2 Recombinant Finder

What's this?

Is it already usable?

Example output

Requirements and Installation

Basic Usage

No output / some sequences not shown

Advanced Usage

Interpreting the output

Source material attribution

TODO / IDEAS / PLANS

Owner

Lena Schimmel

Rethinking Nearest Neighbors for Visual Classification

OpenMMLab Model Deployment Toolset

Multi-objective gym environments for reinforcement learning.

Denoising Normalizing Flow

Combinatorial model of ligand-receptor binding

Black box hyperparameter optimization made easy.

Source code for our paper "Learning to Break Deep Perceptual Hashing: The Use Case NeuralHash"

Code repository of the paper Neural circuit policies enabling auditable autonomy published in Nature Machine Intelligence

PyTorch implementation of CVPR 2020 paper (Reference-Based Sketch Image Colorization using Augmented-Self Reference and Dense Semantic Correspondence) and pre-trained model on ImageNet dataset

The official repository for Deep Image Matting with Flexible Guidance Input

Degree-Quant: Quantization-Aware Training for Graph Neural Networks.

Vehicles Counting using YOLOv4 + DeepSORT + Flask + Ngrok

Neural Logic Inductive Learning

[SIGGRAPH 2020] Attribute2Font: Creating Fonts You Want From Attributes

Machine Learning From Scratch. Bare bones NumPy implementations of machine learning models and algorithms with a focus on accessibility. Aims to cover everything from linear regression to deep learning.

Implementing DropPath/StochasticDepth in PyTorch

Code and Resources for the Transformer Encoder Reasoning Network (TERN)

Official code for UnICORNN (ICML 2021)

DCGAN-tensorflow - A tensorflow implementation of Deep Convolutional Generative Adversarial Networks

Additional environments compatible with OpenAI gym