diff --git a/tutorials/README.md b/tutorials/README.md
index 78ebd40..e9cdb3f 100644
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@@ -122,7 +122,7 @@ These notebooks were created to run in Google Colab, so if you run them in Googl
 You can interact with Google Batch directly to submit commands, or more commonly you can interact with it through orchestration engines like [Nextflow](https://www.nextflow.io/docs/latest/google.html) and [Cromwell](https://cromwell.readthedocs.io/en/latest/backends/GCPBatch/), etc. We have tutorials that utilize Google Batch using [Nextflow](/tutorials/notebooks/GoogleBatch/nextflow) where we run the nf-core Methylseq pipeline, as well as several from the NIGMS Sandbox including [transcriptome assembly](https://github.com/NIGMS/rnaAssemblyMDI), [multiomics](https://github.com/NIGMS/MultiomicsUND), [methylseq](https://github.com/NIGMS/MethylSeqUH), and [metagenomics](https://github.com/NIGMS/MetagenomicsUSD).
 
 ## **Using the Life Sciences API (depreciated)** <a name="lsapi"></a>
-__Life Science API is depreciated on GCP and will no longer be available by July 8, 2025 on the platform,__ we recommend using Google Batch instead. For now you can still interact with the Life Sciences API directly to submit commands, or more commonly you can interact with it through orchestration engines like [Snakemake](https://snakemake.readthedocs.io/en/stable/executing/cloud.html), as of now this workflow manager only supports Life Sciences API.
+__Life Science API is depreciated on GCP and will no longer be available by July 8, 2025 on the platform,__ we recommend using Google Batch instead. For now you can still interact with the Life Sciences API directly to submit commands, or more commonly you can interact with it through orchestration engines like [Snakemake](https://snakemake.readthedocs.io/en/v7.0.0/executor_tutorial/google_lifesciences.html), as of now this workflow manager only supports Life Sciences API.
 
 ## **Public Data Sets** <a name="pub"></a>
 Google has a lot of public datasets available that you can use for your testing. These can be viewed [here](https://cloud.google.com/life-sciences/docs/resources/public-datasets) and can be accessed via [BigQuery](https://cloud.google.com/bigquery/public-data) or directly from the cloud bucket. For example, to view Phase 3 1000 Genomes at the command line type `gsutil ls gs://genomics-public-data/1000-genomes-phase-3`.