Jash271's Stars
Ileriayo/markdown-badges
Badges for your personal developer branding, profile, and projects.
pyro-ppl/pyro
Deep universal probabilistic programming with Python and PyTorch
mtdvio/every-programmer-should-know
A collection of (mostly) technical things every software developer should know about
NAalytics/Assemblies-of-putative-SARS-CoV2-spike-encoding-mRNA-sequences-for-vaccines-BNT-162b2-and-mRNA-1273
RNA vaccines have become a key tool in moving forward through the challenges raised both in the current pandemic and in numerous other public health and medical challenges. With the rollout of vaccines for COVID-19, these synthetic mRNAs have become broadly distributed RNA species in numerous human populations. Despite their ubiquity, sequences are not always available for such RNAs. Standard methods facilitate such sequencing. In this note, we provide experimental sequence information for the RNA components of the initial Moderna (https://pubmed.ncbi.nlm.nih.gov/32756549/) and Pfizer/BioNTech (https://pubmed.ncbi.nlm.nih.gov/33301246/) COVID-19 vaccines, allowing a working assembly of the former and a confirmation of previously reported sequence information for the latter RNA. Sharing of sequence information for broadly used therapeutics has the benefit of allowing any researchers or clinicians using sequencing approaches to rapidly identify such sequences as therapeutic-derived rather than host or infectious in origin. For this work, RNAs were obtained as discards from the small portions of vaccine doses that remained in vials after immunization; such portions would have been required to be otherwise discarded and were analyzed under FDA authorization for research use. To obtain the small amounts of RNA needed for characterization, vaccine remnants were phenol-chloroform extracted using TRIzol Reagent (Invitrogen), with intactness assessed by Agilent 2100 Bioanalyzer before and after extraction. Although our analysis mainly focused on RNAs obtained as soon as possible following discard, we also analyzed samples which had been refrigerated (~4 ℃) for up to 42 days with and without the addition of EDTA. Interestingly a substantial fraction of the RNA remained intact in these preparations. We note that the formulation of the vaccines includes numerous key chemical components which are quite possibly unstable under these conditions-- so these data certainly do not suggest that the vaccine as a biological agent is stable. But it is of interest that chemical stability of RNA itself is not sufficient to preclude eventual development of vaccines with a much less involved cold-chain storage and transportation. For further analysis, the initial RNAs were fragmented by heating to 94℃, primed with a random hexamer-tailed adaptor, amplified through a template-switch protocol (Takara SMARTerer Stranded RNA-seq kit), and sequenced using a MiSeq instrument (Illumina) with paired end 78-per end sequencing. As a reference material in specific assays, we included RNA of known concentration and sequence (from bacteriophage MS2). From these data, we obtained partial information on strandedness and a set of segments that could be used for assembly. This was particularly useful for the Moderna vaccine, for which the original vaccine RNA sequence was not available at the time our study was carried out. Contigs encoding full-length spikes were assembled from the Moderna and Pfizer datasets. The Pfizer/BioNTech data [Figure 1] verified the reported sequence for that vaccine (https://berthub.eu/articles/posts/reverse-engineering-source-code-of-the-biontech-pfizer-vaccine/), while the Moderna sequence [Figure 2] could not be checked against a published reference. RNA preparations lacking dsRNA are desirable in generating vaccine formulations as these will minimize an otherwise dramatic biological (and nonspecific) response that vertebrates have to double stranded character in RNA (https://www.nature.com/articles/nrd.2017.243). In the sequence data that we analyzed, we found that the vast majority of reads were from the expected sense strand. In addition, the minority of antisense reads appeared different from sense reads in lacking the characteristic extensions expected from the template switching protocol. Examining only the reads with an evident template switch (as an indicator for strand-of-origin), we observed that both vaccines overwhelmingly yielded sense reads (>99.99%). Independent sequencing assays and other experimental measurements are ongoing and will be needed to determine whether this template-switched sense read fraction in the SmarterSeq protocol indeed represents the actual dsRNA content in the original material. This work provides an initial assessment of two RNAs that are now a part of the human ecosystem and that are likely to appear in numerous other high throughput RNA-seq studies in which a fraction of the individuals may have previously been vaccinated. ProtoAcknowledgements: Thanks to our colleagues for help and suggestions (Nimit Jain, Emily Greenwald, Lamia Wahba, William Wang, Amisha Kumar, Sameer Sundrani, David Lipman, Bijoyita Roy). Figure 1: Spike-encoding contig assembled from BioNTech/Pfizer BNT-162b2 vaccine. Although the full coding region is included, the nature of the methodology used for sequencing and assembly is such that the assembled contig could lack some sequence from the ends of the RNA. Within the assembled sequence, this hypothetical sequence shows a perfect match to the corresponding sequence from documents available online derived from manufacturer communications with the World Health Organization [as reported by https://berthub.eu/articles/posts/reverse-engineering-source-code-of-the-biontech-pfizer-vaccine/]. The 5’ end for the assembly matches the start site noted in these documents, while the read-based assembly lacks an interrupted polyA tail (A30(GCATATGACT)A70) that is expected to be present in the mRNA.
Juliest88/mysql-node-express
krishnaik06/Feature-Engineering-Live-sessions
jaypajji4444/Zoom-clone-nodej
AI4Bharat/Indic-BERT-v1
Indic-BERT-v1: BERT-based Multilingual Model for 11 Indic Languages and Indian-English. For latest Indic-BERT v2, check: https://github.com/AI4Bharat/IndicBERT
aaronwangy/Data-Science-Cheatsheet
A helpful 5-page machine learning cheatsheet to assist with exam reviews, interview prep, and anything in-between.
PaddlePaddle/PaddleOCR
Awesome multilingual OCR toolkits based on PaddlePaddle (practical ultra lightweight OCR system, support 80+ languages recognition, provide data annotation and synthesis tools, support training and deployment among server, mobile, embedded and IoT devices)
charliegerard/whereami.js
Node.js module to predict indoor location using machine learning and WiFi information 📶
benawad/dogehouse
Taking voice conversations to the moon 🚀
reviewdog/action-tflint
Run tflint with reviewdog on pull requests to enforce best practices
reviewdog/reviewdog
🐶 Automated code review tool integrated with any code analysis tools regardless of programming language
tenable/terrascan
Detect compliance and security violations across Infrastructure as Code to mitigate risk before provisioning cloud native infrastructure.
charliegerard/gaze-detection
👀 Use machine learning in JavaScript to detect eye movements and build gaze-controlled experiences.
georgezouq/awesome-ai-in-finance
🔬 A curated list of awesome LLMs & deep learning strategies & tools in financial market.
aws-samples/aws-kube-code-service
The Code Services Continuous Deployment reference architecture demonstrates how to achieve continuous deployment of an application to a Kubernetes cluster using AWS CodePipeline, AWS CodeCommit, AWS CodeBuild and AWS Lambda.
jasmcaus/opencv-course
Learn OpenCV in 4 Hours - Code used in my Python and OpenCV course on freeCodeCamp.
ccoenraets/react-trader
Sample application built with React and Socket.io
amirsanni/Video-Call-App-NodeJS
A conference call implementation using WebRTC, Socket.io and Node.js
bradtraversy/design-resources-for-developers
Curated list of design and UI resources from stock photos, web templates, CSS frameworks, UI libraries, tools and much more
pypa/pip
The Python package installer
YJDoc2/CodeBook
A facebook like website, for coding. User can follow other users, create and share coding challenges, compile code online, and attempt challenges posted by others.
sudheerj/javascript-interview-questions
List of 1000 JavaScript Interview Questions
openvinotoolkit/open_model_zoo
Pre-trained Deep Learning models and demos (high quality and extremely fast)
lucidrains/DALLE-pytorch
Implementation / replication of DALL-E, OpenAI's Text to Image Transformer, in Pytorch
Jash271/Myntra_Image_Search_Emulation
A Mockup to imitate Myntra's Image Search 👔
AbdaliDahir/gatsby-portfolio
creative personal & portfolio template based on gatsby. designed so you can showcase your work and write your blogs.
jainaman224/Algo_Ds_Notes
A comprehensive resource for learning and implementing algorithms and data structures. This repository includes detailed notes, complexity analysis, and code examples in C++, Java, Python, and more. Ideal for students, professionals, and those preparing for coding interviews.