Pichon Lab Paper is out in Nature Comm!

We are pleased to announce that the Le Pichon lab has recently published their single-nucleus cholinergic sequencing data in Nature Communications! Their data is featured on this site, and available to download as an integrated resource along with our (Gitler Lab) data. Big congratulations to Alkaslasi et al. for a fantastic and impactful paper! Read it here!

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Data Integration with the Le Pichon Lab!

We are very excited to announce that we have gotten together with Claire Le Pichon's Lab , who used different methods to perform similar experiments in parallel to our work. While the markers that they chose to validate were slightly different from ours, the data are extremely concordant and reinforce the fundamental nature of our collective findings. We are currently working to integrate the datasets and make them all publicly available for browsing via cellxgene, as well as for download as a processed and integrated file. Look out for more exciting work from the Le Pichon lab moving forward, and follow Dr. Le Pichon and first authors Mor Alkaslasi and Zoe Piccus on twitter!

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Processed matrix download links

We have received several comments from collaborators and interested parties that the raw .h5 and .fastq formats that we made available on GEO are unnecessarily cumbersome, as they require a large amount of computing power to integrate and cluster a large number of cells. To streamline data sharing, we have added a Download link for the processed .h5d matrices (with cluster ID and annotations) in a .zip file. This link has also been added to the Downloads bar on the More Information tab!

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COMING SOON--Check back to this blog for site changes and analysis improvements. We are currently working on adding epigenetic accessibility to our existing dataset, as well as examining how subtypes of motor neurons respond in neurodegenerative disease (in animal models as well as postmortem human samples). Feel free to leave send comments to jablum(at)stanford(dot)edu with suggestions or thoughts. We are very open to collaboration and look forward to your feedback!

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This work was carried out by the Gitler Lab, in collaboration with the Kaltschmidt and Greenleaf Labs.

Blum et al. 2021--read the paper here.

A parallel study was conducted by the Le Pichon Lab

Alkaslasi et al. 2021--read the preprint here