Welcome to Drop-seq!


Drop-seq is a technology that allows biologists to analyze genome-wide gene expression in thousands of individual cells in a single experiment.  This work is described in Macosko et al., Cell, 2015.  This site provides interested users with resources to implement Drop-seq in their own labs.  We hope you do amazing things with Drop-seq.  Tell us about it!

If you would like to be informed of new protocol optimizations, discussion forums, etc., please send an email to dropseq@gmail.com and we’ll put you on the list. We even have a Google Groups forum dedicated to discussing Drop-seq. Email us to join!


Do you currently have Drop-seq working?  

We are trying to gauge the level of adoption of the technology and would very much appreciate hearing about your experiences.  If you have Drop-seq working, please email dropseq@gmail.com with a picture of your first “Barnyard” plot and, if possible, the broad scientific direction/question you are hoping to address with the technology.  We would really love to hear from all of you!


Droplet Formation

Image courtesy of Patrick Stumpf, Matthew Rose-Zerilli, Rosanna Smith, Martin Fischlechner & Jonathan West at the Centre for Hybrid Biodevices & Cancer Sciences Unit at the University of Southampton


Laboratory resources

A Drop-seq setup can be built from widely available lab equipment costing just a few thousand dollars.

A Drop-seq setup can be built from widely available laboratory equipment costing less than ten thousand dollars.  We used this setup to perform the experiments in the Cell paper.

Here is our latest experimental protocol, which includes instructions for building a Drop-seq setup:

Online-Dropseq-Protocol-v.-3.1-Dec-2015.pdf (51018 downloads)


This protocol reflects our current, optimized Drop-seq protocol and so may not match the methods section of the Cell paper, which is a description of the experiments presented in that paper.  This protocol also includes hints, suggestions, and images.

We want this web site to be a “living protocol”.  As people begin to adopt Drop-seq and we learn about their experiences, we will add additional hints and tips to the protocol, releasing updated protocols with a new date.  We will increment the version number only when we change something substantive about the recommendation for a protocol step.  Please contact us with questions or suggestions – we look forward to hearing about new optimizations!

Here are two supplemental protocols that you might find helpful:

Measuring-Droplet-Volume-in-Home-Made-Devices.pdf (4660 downloads)


Aquapel-Treatment-of-Drop-seq-Devices.pdf (4320 downloads)


Once you have all of the startup equipment and are ready to perform your first Drop-seq run, check out our Drop-seq tutorial/troubleshooting page.

Some more detail on obtaining materials:

  • Barcoded beads:  In order to have a scalable, commercial solution available for users, we taught scientists at a local company (Chemgenes) the split-pool oligo synthesis process we describe in the Cell paper.  We have extensively tested these beads in Drop-seq.  We have asked Chemgenes to make these beads available directly to anyone who orders them. The beads will have a catalog number of CSO-2011.
  • Microfluidic devices:  Here you can download the CAD file for the co-flow microfluidics device, which was designed by our colleague Anindita Basu in the labs of Aviv Regev and David Weitz.  This is a passive-flow PDMS device that could be synthesized in any academic or commercial microfluidics facility.
  • Microfluidic devices can be purchased ready-made from two companies: Nanoshift and FlowJEM.  Simply tell them you’re interested in ordering the latest Drop-seq devices for a quote.  See our FAQ page for more information.


Computational resources

Download here our latest cookbook for core computational analysis of Drop-seq data, which shows you how to transform raw sequence data into an expression measurement for each gene in each individual cell (Drop-seqAlignmentCookbookv1.2Jan2016).  The software was developed by Jim Nemesh in our lab, and the current implementation can be found here ( Drop-seq_tools-1.13.zip (23 downloads) ).  We will add updates (and revise the protocol date) whenever we see opportunities to make something clearer.  We will increment the version number whenever we revise the software or change something substantive about the recommended series of steps.

Core computational flow for Drop-Seq analysis

Core computational flow for Drop-Seq analysis

We further analyze the resulting data using our colleague Rahul Satija’s fantastic single-cell analysis package Seurat (developed while in Aviv Regev’s lab), which produced all of the clustering analyses in the Cell paper.


We have started to receive questions and comments from interested users.  This FAQ provides helpful information for those interested in the Drop-seq technology.

Data sets

We have deposited all of the raw and processed data sets from the Drop-seq experiments described in the Cell paper in Gene Expression Omnibus, accession GSE63473.

These links direct you to the alignment references used in our paper for MOUSE, HUMAN, and MIXED (human+mouse).


Retina Data Set from Macosko et al, 2015

Expression plots for the retina data set are coming soon.

Cluster assignments for the 44,808 retinal cells in the paper are here.



Please email questions to dropseq@gmail.com.  We’ll do our best to answer them!





Melissa Goldman, Steve McCarroll, Evan Macosko, Jim Nemesh, Alec Wysoker