Bulk RNA-sequencing
An end-to-end solution to identify differentially expressed genes, functional annotations and pathways
Overview
Data infrastructure and tools to answer key biological questions about the transcriptional state of your samples.
Answer Biological Questions
What are the gene counts in my sample?
What are the differentially expressed genes between conditions?
What are the associated pathways, function or ontology information associated with key genes or gene sets?
Join leading biopharma companies who analyze their RNAseq data on Latch
The number of drug targets in our pipeline has tripled.”
CSO @ Doloromics
It brought our analysis costs down by 80%”
CSO @ ElsieBio
Go from FastQ → publication-quality results in minutes
80% cheaper than CROs
Analysis Lifecycle
Store Sequencing Data
Scalable, cloud-native storage for FastQ files. A central location to organize teams. Graphical interface for scientists + CLI for programmers
Mount S3 / GCP buckets, integrate with Illumina Basespace, drag and drop from laptops, deploy custom upload scripts from local servers
Automatic QC reports that run on data upload. Accessible on double-click to scientists.
Capture Experimental Metadata
Associate drug treatments, cell lines and other metadata with raw sequencing files in structured schemas.
Graphical control and accessibility of tables by scientists.
Project management features to organize data by experiment and biological focus.
Generate Gene Counts
Use the nf-core/rnaseq workflow to perform QC, trimming, (pseudo) alignment. Produce a gene count matrix and QC reports.
Scale to hundreds of samples and pay for only the computing resources you use.
Scientists upload and edit graphical sample sheets to run bioinformatics workflows.
Pull in error-validated and typed metadata to fill out workflow parameters.
Identify Differentially Expressed Genes
Run DeSeq2 to identify transcriptionally distinct features between biological samples. Explore downstream visualizations in your browser, with the flexibility to alter and customize results.
Construct condition groups in a graphical interface.
Use fold change measurements to interactively identify deferentially-expressed genes of interest (GOI) between conditions. Flexibly select gene panels for publication-ready heat map visualizations.
Analyze Counts in Notebooks
Read in your counts file from a shared filesystem and analyze / plot counts with exploratory Python libraries like seaborn and pandas.
Looking for an easier solution?
Eliminate manual clicking and user error with an automated plotting solution for your lab.
7-Day Free Trial
Access the leading data platform for biology.
- A scoping call to map out your scientific workflows
- Access a curated workspace customized to your assays and needs
- Live 16/6 support with a Latch bioinformatics engineer
- A hands-on onboarding session to train your team