Analysis of Antarctica sequencing samples contaminated with SARS-CoV-2

Overview

Analysis of SARS-CoV-2 reads in sequencing of 2018-2019 Antarctica samples in PRJNA692319

The samples analyzed here are described in this preprint, which is a pre-print by Istvan Csabai and co-workers that describes SARS-CoV-2 reads in samples from Antarctica sequencing in China. I was originally alerted to the pre-print by Carl Zimmer on Dec-23-2021. Istvan Csabai and coworkers subsequently posted a second pre-print that also analyzes the host reads.

Repeating key parts of the analysis

The code in this repo independently repeats some of the analyses.

To run the analysis, build the conda environment in environment.yml and then run the analysis using Snakefile. To do this on the Hutch cluster, using run.bash:

sbatch -c 16 run.bash

The results are placed in the ./results/ subdirectory. Most of the results files are not tracked due to file-size limitations, but the following key files are tracked:

  • results/alignment_counts.csv gives the number of reads aligning to SARS-CoV-2 for each sample. This confirms that three accessions (SRR13441704, SRR13441705, and SRR13441708) have most of the SARS-CoV-2 reads, although a few other samples also have some.
  • results/variant_analysis.csv reports all variants found in the samples relative to Wuhan-Hu-1.
  • results/variant_analysis_to_outgroup.csv reports the variants found in the samples that represent mutations from Wuhan-Hu-1 towards the two closest bat coronavirus relatives, RaTG13 and BANAL-20-52. Note that some of the reads contain three key mutations relative to Wuhan-Hu-1 (C8782T, C18060T, and T28144C) that move the sequence closer to the bat coronavirus relatives. These mutations define one of the two plausible progenitors for all currently known human SARS-CoV-2 sequences (see Kumar et al (2021) and Bloom (2021)).

Archived links after initially hearing about pre-print

I archived the following links on Dec-23-2021 after hearing about the pre-print from Carl Zimmer:

Deletion of some samples from SRA

On Jan-3-2022, I received an e-mail one of the pre-print authors, Istvan Csabai, saying that three of the samples (appearing to be the ones with the most SARS-CoV-2 reads) had been removed from the SRA. He also noted that bioRxiv had refused to publish their pre-print without explanation; the file he attached indicates the submission ID was BIORXIV-2021-472446v1. I confirmed that three of the accessions had indeed been removed from the SRA as shown in the following archived links:

I also e-mailed Richard Sever at bioRxiv to ask why the pre-print was rejected, and explained I had repeated and validated the key findings. Richard Sever said he could not give details about the pre-print review process, but that in the future the authors could appeal if they thought the rejection was unfounded.

Details from Istvan Csabai

On Jan-4-2022, I chatted with Istvan Csabai. He had contacted the authors of the pre-print, and shared their reply to him. The authors had prepped the samples in early 2019, and submitted to Sangon BioTech for sequencing in December, getting the results back in early January.

Second pre-print from Csabai and restoration of deleted files

Istvan Csabai then worked on a second pre-print that analyzed host reads and made various findings, including co-contamination with African green monkey (Vero?) and human DNA. He sent me pre-print drafts on Jan-16-2022 and on Jan-24-2022, and I provided comments on both drafts and agreed to be listed in the Acknowledgments.

On Feb-3-2022, Istvan Csabai told me that the second pre-print had also been rejected from bioRxiv. Because I had previously contacted Richard Sever when I heard the first pre-print was rejected, I suggested Istvan could CC me on an e-mail to Richard Sever appealing the rejection, which he did. Unfortunately, Richard Sever declined the appeal, so instead Istvan posted the pre-print on Resarch Square.

At that point on Feb-3-2022, I also re-checked the three deletion accessions (SRR13441704, SRR13441705, and SRR13441708). To my surprise, all three were now again available by public access. Here are archived links demonstrating that they were again available:

I confirmed that the replaced accessions were identical to the deleted ones.

Inquiry to authors of PRJNA692319

On Feb-8-2022, I e-mailed the Chinese authors of the paper to ask about the sample deletion and restoration. They e-mailed back almost immediately. They confirmed what they had told Istvan: they had sequenced the samples with Sangon Biotech (Shanghai) after extracting the DNA in December 2019 from their samples. The suspect that contamination of the samples happened at Sangon Biotech. They deleted the three most contaminated samples from the Sequence Read Archive. They do not know why the samples were then "un-deleted."

Owner
Jesse Bloom
I research the evolution of viruses and proteins.
Jesse Bloom
Bayesian inference for Permuton-induced Chinese Restaurant Process (NeurIPS2021).

Permuton-induced Chinese Restaurant Process Note: Currently only the Matlab version is available, but a Python version will be available soon! This is

NTT Communication Science Laboratories 3 Dec 17, 2022
An efficient toolkit for Face Stylization based on the paper "AgileGAN: Stylizing Portraits by Inversion-Consistent Transfer Learning"

MMGEN-FaceStylor English | 简体中文 Introduction This repo is an efficient toolkit for Face Stylization based on the paper "AgileGAN: Stylizing Portraits

OpenMMLab 182 Dec 27, 2022
NaijaSenti is an open-source sentiment and emotion corpora for four major Nigerian languages

NaijaSenti is an open-source sentiment and emotion corpora for four major Nigerian languages. This project was supported by lacuna-fund initiatives. Jump straight to one of the sections below, or jus

Hausa Natural Language Processing 14 Dec 20, 2022
Hooks for VCOCO

Verbs in COCO (V-COCO) Dataset This repository hosts the Verbs in COCO (V-COCO) dataset and associated code to evaluate models for the Visual Semantic

Saurabh Gupta 131 Nov 24, 2022
Swapping face using Face Mesh with TensorFlow Lite

Swapping face using Face Mesh with TensorFlow Lite

iwatake 17 Apr 26, 2022
MLPs for Vision and Langauge Modeling (Coming Soon)

MLP Architectures for Vision-and-Language Modeling: An Empirical Study MLP Architectures for Vision-and-Language Modeling: An Empirical Study (Code wi

Yixin Nie 27 May 09, 2022
Quantized models with python

quantized-network download .pth files to qmodels/: googlenet : https://download.

adreamxcj 2 Dec 28, 2021
Official code of our work, AVATAR: A Parallel Corpus for Java-Python Program Translation.

AVATAR Official code of our work, AVATAR: A Parallel Corpus for Java-Python Program Translation. AVATAR stands for jAVA-pyThon progrAm tRanslation. AV

Wasi Ahmad 26 Dec 03, 2022
Artificial Intelligence playing minesweeper 🤖

AI playing Minesweeper ✨ Minesweeper is a single-player puzzle video game. The objective of the game is to clear a rectangular board containing hidden

Vaibhaw 8 Oct 17, 2022
🚩🚩🚩

My CTF Challenges 2021 AIS3 Pre-exam / MyFirstCTF Name Category Keywords Difficulty ⒸⓄⓋⒾⒹ-①⑨ (MyFirstCTF Only) Reverse Baby ★ Piano Reverse C#, .NET ★

6 Oct 28, 2021
Implementation of ViViT: A Video Vision Transformer

ViViT: A Video Vision Transformer Unofficial implementation of ViViT: A Video Vision Transformer. Notes: This is in WIP. Model 2 is implemented, Model

Rishikesh (ऋषिकेश) 297 Jan 06, 2023
Cortex-compatible model server for Python and TensorFlow

Nucleus model server Nucleus is a model server for TensorFlow and generic Python models. It is compatible with Cortex clusters, Kubernetes clusters, a

Cortex Labs 14 Nov 27, 2022
Train a state-of-the-art yolov3 object detector from scratch!

TrainYourOwnYOLO: Building a Custom Object Detector from Scratch This repo let's you train a custom image detector using the state-of-the-art YOLOv3 c

AntonMu 616 Jan 08, 2023
Process text, including tokenizing and representing sentences as vectors and Applying some concepts like RNN, LSTM and GRU to create a classifier can detect the language in which a sentence is written from among 17 languages.

Language Identifier What is this ? The goal of this project is to create a model that is able to predict a given sentence language through text proces

Hossam Asaad 9 Dec 15, 2022
Code for "FGR: Frustum-Aware Geometric Reasoning for Weakly Supervised 3D Vehicle Detection", ICRA 2021

FGR This repository contains the python implementation for paper "FGR: Frustum-Aware Geometric Reasoning for Weakly Supervised 3D Vehicle Detection"(I

Yi Wei 31 Dec 08, 2022
R interface to fast.ai

R interface to fastai The fastai package provides R wrappers to fastai. The fastai library simplifies training fast and accurate neural nets using mod

113 Dec 20, 2022
YoloV3 Implemented in Tensorflow 2.0

YoloV3 Implemented in TensorFlow 2.0 This repo provides a clean implementation of YoloV3 in TensorFlow 2.0 using all the best practices. Key Features

Zihao Zhang 2.5k Dec 26, 2022
Python port of R's Comprehensive Dynamic Time Warp algorithm package

Welcome to the dtw-python package Comprehensive implementation of Dynamic Time Warping algorithms. DTW is a family of algorithms which compute the loc

Dynamic Time Warping algorithms 154 Dec 26, 2022
SegTransVAE: Hybrid CNN - Transformer with Regularization for medical image segmentation

SegTransVAE: Hybrid CNN - Transformer with Regularization for medical image segmentation This repo is the official implementation for SegTransVAE. Seg

Nguyen Truong Hai 4 Aug 04, 2022
An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional Filters

CNN-Filter-DB An Empirical Investigation of Model-to-Model Distribution Shifts in Trained Convolutional Filters Paul Gavrikov, Janis Keuper Paper: htt

Paul Gavrikov 18 Dec 30, 2022