LatchBio

Programmable gene editing proteins have transformed bioengineering. Cheap and widespread access to new families of engineered nucleases have given us genetic medicines and genome-scale screens. We trace the end-to-end engineering of a CRISPR library on an AI-enabled data infrastructure, including: - Batched design of gRNAs on GPU clusters - Exploring off-target statistics with natural language prompts - Validating the edit behavior of single guides from PCR amplicon data - Analyzing large scale screens and building dashboards to communicate results - Identifying the function of key genes from the screen with natural language prompts Throughout this flow, we will accomplish concrete biological objectives: - Search for potential off-target sites of RNA-guided endonucleases - Quantify insertions, mutations and deletions from genome editing proteins - Identify important genes from CRISPR knockout screens Read more - https://lnkd.in/gZun7Uh3

Last month we released our first Product Digest newsletter! Check out our October edition to read about a few of our latest product releases and upcoming events with our partners including our: ?Native support for Nextflow ?White-labeled customer analysis portals for solution providers. ?End-to-end flows for Bulk RNA-seq, qPCR, and ATAC-seq ?Our upcoming one-day conference in Boston on October 21st Read the October edition here: https://lnkd.in/gW2N4gvn Be sure to subscribe to our newsletter to stay tuned for our November Product Digest!

Data infrastructure is the digital brick and mortar of biotech. New spatial, single-cell and proteomic assays are exploding in size. Useful machine learning is coming online. Large scale data generation is driving scientific decision making. In this new age of data-driven biology, the industry is adopting software platforms that manage and synthesize new classes of experimental data. Data infrastructure enables iterative feedback loops between the bench and computer, cross-disciplinary access to data and library-scale target discovery, molecular design & validation. LatchBio is hosting a free one-day conference for incredible biotechs & solution providers to pool their knowledge and discuss the use of these systems to solve practical industry problems. Speakers include: Jordan Christensen, SVP Technology at Recursion Danny Wells, Founder; previously CTO at Santa Ana Bio, Inc. & Immunai Robert Policastro, PhD, Senior Scientist at Ensoma Eddie Abrams, CIO of BigHat Biosciences TJ Bollerman, Head of Engineering at Enveda Biosciences Colin Ng + James McGann, Founding Scientist + VP at AtlasXomics Inc. David Levy-Booth, Data Engineering Lead at Dyno Therapeutics Jesse Johnson, Founder of Merelogic / Scaling Biotech Dillon Flood, Founder of ElsieBio (a subsidiary of GSK) Apply at conference.latch.bio. Speakers from Recursion, Ensoma, Elsie x GSK, Dyno Tx, BigHat.

We talked to over fifty -omics tools providers. No one is handling the current data explosion. But everyone is causing it. Over the past year, the talk of leadership is shifting dramatically: ?- Last year, 1 million cell sequencing, now 2 million cells, soon 10 million cells. ?- Last year, 1 -omics modality, now 2 overlaid, soon 5 fully integrated ?- Last year, 1 NVIDIA GPU, now 4 NVIDIA A10s, soon 10 NVIDIA A100s The volume of data is exploding, and the collective vision of CEOs is expanding. But scientists can't even analyze their current data without serious delays from computational cores. Biotechs are taking weeks or months to get insight. How are providers solving this? The answer lies in engineering the clouds ????. The major clouds (AWS, Azure, GCP) offer virtually unlimited scale, enabling two classes of solutions built on top: 1. Cloud platforms built in-house. These clouds require millions in investment and are designed to be: - User-facing - Turnkey for custom assays (multi-omics kits, instruments, etc.)? - Scalable - Accessible - Customizable - Cloud-native (AWS, GCP, Azure)? - Secure & compliant Examples include the 10x Genomics cloud or Illumina's BaseSpace. (Each platform took 20+ engineers and several years to build – no small feat.) 2. The second class is biological cloud platform providers, like LatchBio, DNANexus, or BasePair. These platforms allow you to white label your own custom bioinformatics solution, without building entire engineering teams: - All of the above - Data visualizations - White labeling - IT administration - Usage-based pricing - Developer kits (nextflow, python, snakemake) Every provider in the -omics space needs one of these two solutions to meet the demands of growth. Both for internal R&D and customer-facing use. The choice between the two isn't simple. To help providers caught in this dilemma, we wrote a guide to evaluating your needs. Link is in the comments.?Please give a read and let us know your feedback!

A few months ago, we presented the first comprehensive map of the Omics Solution Provider landscape. Today we’re introducing version 2! Thanks to everyone who left feedback on our original version, we’re able to present an even more detailed view of the market.? For the sake of being concise, we were reductive in the last market map. We tried to fit each company squarely into one category, but the truth is that most solution providers are offering a combination of services, instruments, and kits within their area(s) of expertise. Our new market map highlights companies multiple times, within each solution section that they offer. The conversation around our last map also helped introduce us to a few companies we had missed, which we’d like to highlight: Aliri Bioanalysis, a global bioanalytical CRO that provides a range of bioanalysis laboratory and spatial imaging solutions. Advanced Cell Diagnostics (ACD), a Bio-Techne brand, is a pioneer and leader in the advancement of spatial genomics by unlocking the power of RNA and developing cell- and tissue- based research. Miltenyi Biotec offers research- and clinical-grade products, services, and instruments for sample preparation, cell separation, flow cytometry, and cell culture applications. Singleron Biotechnologies provides comprehensive single-cell multi-omics solutions including user-friendly kits, instruments, and services for enhanced clinical and molecular research. BioSkryb Genomics provides kits and services to give a comprehensive view of the genome, transcriptome, and targeted proteins. Depixus is pioneering a revolutionary single molecular analysis platform that employs magnetic force spectroscopy to probe complex biomolecular interactions, unlocking critical and unique structural insights. Evotec is an R&D biotech that offers accelerating, high value pipeline co-creation partnerships and CRO/CDMO services. Biognosys offers next generation proteomics solutions based on proprietary mass spectrometry technology. CellCarta provides high-end scientific capabilities, multiple platforms, and regulatory expertise to support all phases of therapeutics development. Emerald Cloud Lab provides full software controlled, highly automated life science laboratories that allow scientists to design, execute, and analyze experiments remotely from anywhere on earth. SHIMADZU CORPORATION is a Japanese company manufacturing precision instruments, measuring instruments, and medical equipment. Eurofins Genomics is an international provider of DNA sequencing service, oligonucleotide synthesis products, and bioinformatic services. Sequentify develops genomic samples processing products and technologies, prior to sequencing hardware loading. As always, please let me know any thoughts or feedback.

Nextflow is the most popular language to write and scale bioinformatics workflows. We have listened to and pledge our support to the community. LatchBio is releasing a native Nextflow integration. New tools to develop + host workflows for scientific teams. Developers can drop-in existing Nextflow projects, and configure their workflow in 3 steps: 1. Generate a single Python file from Nextflow code to configure your interface 2. Modify or extend this file 3. Register the workflow with Latch Access new tools to develop and host Nextflow: - Visualize and explore the execution graph - Resource dashboards to optimize cost and runtime - Associate workflow versions with Git commits. - Use secure, private container repositories Integrate into upstream and downstream components of the end-to-end analysis lifecycle: - Pull structured metadata captured from the wet lab - Analyze outputs in managed Jupyter + Rstudio instances - Build dashboards to communicate workflow results LatchBio is usage based. We want your entire team to access and understand your data and analysis. No seat-based fees or licenses. Read more - https://lnkd.in/g4JNEqnX

Kit providers are enabling exploration of the farthest boundaries of biological possibilities by transforming cutting-edge biological solutions into accessible kits. However, these kits can generate 100s of TBs of data that can take months and vast computational infrastructure to turn into insights. Listen to Colin Ng, VP of AtlasXomics Inc., describe how quickly their customers can explore insights from raw data on Latch.?

We have learned over the past decade that sequencing RNA and DNA is not enough to develop drugs or understand basic biology. There are many experimental techniques that help scientists understand the epigenome, but?ATAC-seq?is likely the most widespread. However, making sense of this data is difficult, and running bioinformatics workflows is only a small piece of the full analysis lifecycle. The goal of ATAC-seq is to locate peaks of chromatin accessibility across the genome and examine how they change with covariates. This requires software that allows scientists to perform genome-scale operations and render peaks across multiple samples with low latency. To accomplish this, we showcase a suite of tools scientists use to interrogate ATAC-seq data, and outline how they fit into a broader data infrastructure suitable for interdisciplinary collaboration and long term data re-use. We start with the end reports, and work backwards to the sequencer, in a full analysis lifecycle to answer concrete biological questions: - How do peaks of accessible DNA vary between different samples? - Are there enriched motifs or functional annotations associated with these regions? - Where are genomic regions of chromatin accessibility? https://lnkd.in/g6Az_DRU

Avoid copying and pasting between spreadsheets and manually plotting your results. Calculate ΔCq, ΔΔCq, and fold changes, with access to underlying Python, by clicking a button on Latch’s qPCR Template. Test it out yourself with this interactive demo: https://lnkd.in/geQbFZNx

Most of the biotech industry runs on qPCR. Its low cost, simplicity and maturity has established the technique as a staple in many molecular biology workflows. However, the analysis of the downstream data is anything but standard. Most scientists spend hours passing files between Excel and GraphPad Prism, where they analyze data with error-prone spreadsheet calculations and manually plot their results. There is a need for modern analysis tools to manage the full lifecycle of qPCR data, supporting the following core steps: - The central and structured capture of qPCR machine outputs and experimental metadata - An automated and reproducible method for computing Cqs + ??Cqs, and producing plots, backed by Python - Links between raw machine outputs, tables of Cq calculations and final plots Here we present the full analysis lifecycle of qPCR on LatchBio to answer the following biological questions: - How do my raw Cqs vary between wells? - What are the ??Cqs for each condition? - How does the fold change of my target gene change between conditions? Read a deep dive on the analysis lifecycle - https://lnkd.in/g5vWi9rj