Product

The End-to-End Cloud Platform for Biotech Teams.

Hundreds of biotechs use Latch to make data analysis faster, cheaper, more accessible, and instantly accelerate their R&D milestones.

Screenshot of the Latch Platform

The Only Platform You Need

Introducing the four pillars of Latch: Data, Registry, Workflows, and Pods.

DataStorageStore data of any sizeExploreExplore public datasetsRegistrySample SheetsAssociate NGS samples with metadataWorkflowsBatch Execution & User InterfaceUpload and run workflows of any scalePodsAppsHost visualization apps for scientists (RShiny, DashApps, Streamlit)RStudio/JupyterLabsCloud computers for shareable and reproducible analysis

Latch consists of  Latch Data where all your files live,  Latch Registry to associate large files with metadata, a Latch Workflow Orchestrator to orchestrate and create an interface for your own workflows, and  Latch Pods to run exploratory analysis. 

Unlock your team's full potential and elevate your scientific breakthroughs with LatchBio's state-of-the-art platform thanks to unprecedented collaboration, speed, and scale.

Latch Data

A Data Store Accessible to Everyone

Scalable like a cloud storage solution. Easy to use like your computer file system.

Search.../20210710.MISEQ0111Folder, 401 MBCreatedCreated byExecution IDKindTags11/11/2021, 1:30 PMCrispy (Workflow)8DU59DA928D35FolderDataSequencer ImportsBulk RNA-SeqPipeline Outputsdaddy-realnessBaseSpace ImportsYost, et all.pdfFOXP2_protein.pdbFOXP2.2_protein.pdbproperties.xlxsDeSeq Report20210697.MISEQ0111MISEQ0111_S1_L001_R1_001.fastq.gzMISEQ0113_S1_L001_R1_001.fastq.gzMISEQ0112_S1_L001_R1_001.fastq.gzMISEQ0114_S1_L001_R1_001.fastq.gzMISEQ0111_S1_L001_R2_001.fastq.gzMISEQ0113_S1_L001_R2_001.fastq.gzMISEQ0112_S1_L001_R2_001.fastq.gzMISEQ0114_S1_L001_R2_001.fastq.gz20210696.MISEQ011120210695.MISEQ011120210691.MISEQ011120210687.MISEQ011120210683.MISEQ011120210693.MISEQ011120210689.MISEQ011120210685.MISEQ011120210681.MISEQ011120210694.MISEQ013120210690.MISEQ013120210686.MISEQ013120210682.MISEQ013120210692.MISEQ013120210688.MISEQ013120210684.MISEQ013120210680.MISEQ0131RRD-PCR.92910Data ID85DU020PA39PD3Key...Value...UploadExplore DatasetsAccessShare

“My dreams and ambitions exploded with Latch. Latch Data allows our company to collaborate at a scale previously impossible.”

Colin Ng, VP of Business Development, AtlasXOmics

screenshot showing data upload on latch
Onboarding data is easy

Upload data of any size, any type, from anywhere

Drag-and-drop files from your local computer or mount an AWS S3 bucket with your organization’s data on Latch.

Use Latch CLI to stream batches of data from on-premise systems or your computer. Take advantage of Latch SDK and Latch Secrets to securely write workflows to migrate data from GCP and Azure to Latch

screenshot showing datasets avaiable on latch
Obtain public datasets on-demand

Download public datasets

Instantly download any dataset from NCBI’s Sequence Read Archive using
Latch SRA Downloader
Workflow

Access 4,000+ harmonized single-cell datasets via Latch partnership with Elucidata

file history on latch platform
Own your data with confidence

Store data in a secure cloud environment

Achieve data provenance: Every file comes with complete history of creation events to support compliance requirements.

Have fine-grained permission control over who can view, read, and write to files.

previews of files that can be viewed on latch
A file system biologists and bioinformaticians both can love

Visualize multiomics files

NGS files (FastQ, BAM, SAM, VCF, PDB) have default visualizations, such as FastQC, IGV, and Protein Viewer built on top, so you can inspect key insights in seconds, without having to ever leave the Latch platform.

the latch sharing modal
Collaborate better

Share data with anyone

Share terabytes of data as easy as you would on Dropbox or Google Drive. Set flexible sharing permissions (Read, Write, or View-only) with collaborators.

Latch Registry

A Database Interface Accessible to Everyone

Never lose track of mission-critical metadata on NGS files

Screenshot of registry on the latch platform

“With Registry, you can tie all of the sequencing data, strain images, and metadata together in one place. It makes analysis much more comprehensive and enables both scientists and bioinformatics team interface with the same images, sequencing files, and metadata in a table-like format.”

Chris Baldock, Chief Data Officer, Metagen

latch registry table close up screenshot
A collaborative database for everyone

Shared Table Interface for the Wet and Dry Lab

A familiar spreadsheet-like interface that is easy to edit and reference files stored in Latch Data. Embed images or links to reports in the table for quick interpretation of biological data and create parent-child relationships between tables.

latch registry table close up screenshot
Sequencing File Organization at Scale

Organize Sequencing Files with Metadata

Catalog and link files on Latch Data with metadata in a table-like format which allows you to designate strong types to columns in tables to enforce standardization. And import bulk data via a spreadsheet like Excel or CSV

latch registry table close up screenshot
Plugs into your workflows

Launch Batched Analyses from Registry

The rows within Registry tables provide a powerful means for initiating executions, enabling smooth launch processes. Additionally, the Python API offers an automated solution to effortlessly populate Registry tables with the outputs generated from workflows.

latch registry table close up screenshot
Search any files and metadata with ease

Search and filter

Effortlessly search and filter Registry tables to retrieve past data based on specific column and cell values.

...

file_path = Path(file.local_path)
file_size = os.Path(file_path).st_size

tbl = Table(id="1234")
with tbl.update() as updater:
tbl.upsert_record(
record_name,
{
"File": file,
"Size": file_size,
}
)

...
Developer-friendly

Update data with Python API

Registry Python API allows for CRUD (create, read, update, and delete) operations on Registry tables. Read and write to Registry tables from a workflow or notebook environment

Latch Workflow Manager

A Workflow Orchestration Platform for Scalable Analyses

Upload any bioinformatics workflow with flexibility. Empower scientists to self-serve workflows.

Image two
Image one

“Our developer uploaded workflows to Latch that can analyze 100 curves at a time. And all scientists need to do is click a button on Latch. This saves an enormous amount of time, probably a day of work per scientist, 20 days a month of labor.”

Eszter N. Tóth, PhD, Senior Research Scientist, Etcembly

Get user-friendly interface. No extra work.

Auto-generation of workflow interface

Latch SDK is a flexible Python SDK that enables easy portability from existing frameworks and languages to Latch.

Define tasks using pure Python functions and leverage the subprocess module to spawn child processes that execute scripts in any language.

@workflow
def my_workflow(
...
read: LatchFile,
amplicon_sequence: List[String],
quantification_window_center: Union[None, int] = -3,
...
):
...
Select FileReadAmplicon SequenceQuantification Window Center3Amplicon Sequence

Each parameter can be configured by altering its corresponding component (swapping a number field with radio options for common integer values), adding documentation (such as labels and help tooltips), and by changing its order and grouping on the page.

@workflow
def my_workflow(
...
read: LatchFile,
amplicon_sequence: List[String],
quantification_window_center: Union[None, int] = -3,
...
):
...
read:
A fastq file of sequenced reads
__metadata__:
display_name: Reads
appearance:
batch_table_column: true
detail: (.fastq, .fastq.gz)
placeholder: Select a file or input URL/URI...
amplicon_sequence:
The amplicon sequence(s) used for the experiment
__metadata__:
display_name: Amplicon Sequence
appearance:
placeholder: AATTGGCC...
quantification_window_center:
Center of quantification window to use within respect to the 3' end of the provided sgRNA sequence.__metadata__:
display_name: Quantification Window Center
appearance:
multiselect:
options:
- {name: Cas9, value: -3}
- {name: Cpfl1, value: 1}
- {name: Base Editors, value: -10}
allow_custom: true
Select FileRead(.fastq, .fastq.gz)Select a file or enter URL/URI...Amplicon SequenceAmplicon SequenceAATTGGCC...Quantification Window Center(Relative to 3' of sgRNA)Cpfl1 [+1]Base Editors [-10]CustomCas9 [-3]
Scalability

Specify arbitrary resource your workflow needs

Use single-line python task decorators to easily define resources available at runtime.

The framework starts at 2 CPUs and 4 GBs of memory and goes all the way to 31 CPUs, 120 GBs of memory and 1 GPU (24 GBs of VRAM, 9,216 CUDA cores) to easily handle all processing needs.

@latch.medium_gpu_task
def cas_offinder(
...
):


@latch.large_task
def nf_core_rnaseq(
...
):
...

Latch Pods

Scalable, on-demand cloud computers

Productivity and flexibility of a personal computer. Scale of the cloud.

PodsPodMy AppsTemplatesScanpy312A template with Scanpy dependencies for single-cell analysis in PythonCRISPRMITBlurgHaspBioV.0.0.2LeafCutter511Annotation-free quantification of RNA splicingSingle CellUse TemplatePlot and annotate Single Cell RNA-Seq dataDownloadsContributor32 last weekHaspBioMy TemplatesPublic Templates

“Our company is extremely exploratory, I wanted something extremely flexible. I was looking literally for an extension of my personal computer. I needed to be able to write my own code, the way that I know how to do it today, and to connect that to seamlessly memory and compute.”

Jonathan Hsu, Chief Technology Officer, Gensaic

screenshot showing pod storage options on latch
Scalable resources on-demand

Start large cloud computers instantly

It’s that simple - select up to 93 CPU cores, 730 GiB RAM, and 16000 GB of storage and click “Launch”

screenshot showing notebook enviroment on latch
Accessible notebook environment

Run analyses in notebook environments

Built-in Jupyter Lab and RStudio to support Python and R analyses & bash terminals for command-line operations.

...or use it with your favorite IDE — connect to Pods via SSH from your local computers and integrate with a familiar IDE (VSCode, PyCharm, and more) .

screenshot showing pod templates on latch
Reproducibility at its core

Save, share, and reuse compute environments

Once your Pod is set up with dependencies, scripts, and analyses, you can save a snapshot of your Pod into a Pod Template.

All members in the same team workspace can start a new pod from a template. Make pod templates “Public” to share it with the world, or re-use others.

screenshot showing auto shutoff on latch
Be in charge of what you pay

Save cost with auto-shutoff

Fine-grained options to auto shutoff a Pod if there is no network activity to save cost

World-class Customer Support

More than just a platform – an analysis partner

Don’t take our word for it.

The thing with Latch is the customer service is brilliant. No matter how good a platform is, if the customer service is not good, you’re not going to use it. Latch responds right away to literally any question. It’s quite insane actually.”

Eszter Toth - Group leader of Genomics, Etcembly

The people behind Latch and the responsiveness is awesome. I have been very impressed with how fast they respond to us. It feels like we’ve got this entire LatchBio team at our fingertips to solve the problems we’re not equipped to solve. That definitely exceeded expectations.”

Jonathan Hsu - Chief Technical Officer, Gensaic

The support and onboarding we received from latch has been way beyond our expectations. The platform has been a great solution for our complex spatial biology data.”

Colin Ng - Vice President of Business Development, AtlasXomics

How we work with Partners

We take your scientific journey seriously.

With Latch, we map out your entire end-to-end drug discovery campaign. Our engineering team acts as an extension to your company and provides support to migrate all data, workflows, and notebooks upfront. For early-stage companies, our in-house bioinformaticians provide consulting services to get your first analyses up and running as fast as possible. That way, you have more time doing life-saving science, and less time worrying about cloud infrastructure set up.

Accelerate biological insights now