Pricing

Scale as your lab needs grow.

Pay As You Go

Most popular
$25per 10 credits

For individual researchers

  • Credits never expire
  • Files up to 20GB
  • Email support
Contact us

Lab

$99per month

For research groups

  • 100 credits per month
  • Files up to 20GB
  • Email support
Contact us

Enterprise

Custom

For core facilities

  • Unlimited conversions
  • No file size limit
  • Dedicated support
Contact us

How credits work

Each conversion costs credits based on file size. Larger files require more compute time and memory.

File sizeCredits per conversionPay As You Go cost
< 2 GB1 credit$2.50
2 GB - 5 GB2 credits$5.00
5 GB - 10 GB3 credits$7.50
10 GB - 20 GB5 credits$12.50

Frequently asked questions

Can I try it before I pay?

Yes. Files under 100 MB can be converted for free.

What file formats are supported?

Seurat objects (.rds) and AnnData objects (.h5ad). We convert in both directions with full metadata preservation including cell metadata, gene metadata, embeddings, and graphs.

Do credits expire?

Pay As You Go credits never expire. Lab subscription credits reset each billing cycle.

Can I pay with a grant or PO?

Yes. For Lab and Enterprise plans we can invoice against a grant or purchase order. Contact hello@singlecellconvert.com to get set up.

Why is this conversion hard?

Seurat and AnnData were designed with fundamentally different data models. Existing tools like SeuratDisk (archived, unmaintained) and sceasy (drops metadata) fall short. Here's what makes it non-trivial:

Seurat → AnnData

  • Multi-assay vs. single matrix — Seurat natively supports multiple assays (RNA, ADT, ATAC), while AnnData stores a single .X matrix with additional layers
  • Dimensional reductions — Seurat stores PCA, UMAP, and tSNE in named @reductions slots that must map to .obsm
  • Graph storage — Seurat's SNN/NN graphs use a different sparse matrix convention than AnnData's .obsp

AnnData → Seurat

  • Ambiguous .X matrix — The main matrix could be raw counts, log-normalized data, or scaled values. We use heuristics to determine the correct Seurat slot
  • Layer mapping — AnnData layers need to map to the right combination of Seurat's counts, data, and scale.data slots
  • Embedding keys — AnnData uses arbitrary keys in .obsm that must be mapped to Seurat reduction objects with the correct key prefix

Ready to convert?

Files under 100 MB convert for free — no account required.

When you need this

Common scenarios where researchers need to convert between Seurat and AnnData formats.

Seurat → AnnData

  • Your analysis was done in R (Seurat) but you need Python tools like Scanpy, scvi-tools, or CellRank for downstream analysis
  • You want to submit data to a repository that requires .h5ad format, such as CELLxGENE Discover
  • Collaborators work in Python and need your R-processed single-cell data in a native format
  • You need a SeuratDisk alternative since it is archived and no longer maintained

AnnData → Seurat

  • Your analysis was done in Python (Scanpy, scvi-tools) but you need R-based tools like Seurat, Monocle, or CellChat
  • You downloaded data from CELLxGENE (which distributes .h5ad files) and need it in Seurat format
  • Collaborators work in R and need your Python-processed data in a native format