The people in the lab

Christian Schneider

Medical Doctoral Student

Lisa Dravta

Masters Student

Roger Aylagas Torres

Masters Student

Zahra Moslehi

Postdoctoral Researcher

Ece Asirim

Doctoral Student

Irina Khven

Doctoral Student

Alex Lederer

Doctoral Student

Gioele La Manno

Principal Investigator

Halima Hannah Schede

Doctoral Student


Previous members


Popular science, News and Media

Two EPFL life scientists awarded SNSF grants

The lab is the recipient of one of the 79 grants awarded this year across all scientific disciplines. I am really honored by this recognition. This SNF grant will allow us to study, using cutting-edge technologies, the complex cellular dynamics of progenitor cells during brain development.

The lab has been awarded a SPARK SNF grant!

We are honored to have been warded a SNF SPARK grant to work on ‘A novel strategy for optics-free tomography-based spatial molecular profiling of tissues’ SPARK is a new funding scheme designed for projects that show unconventional thinking and introduce a unique approach.

Martin and Ana Marija join EPFL as ELISIR fellows

Martin Weigert and Ana Marija Jakšić will be joining the EPFL as new ELISIR fellows. I was very pleased to hear that not one but two candidates have been selected! Looking forward to having them on campus. Exciting interactions ahead.

The lab has been awarded a Human Cell Atlas CZI grant

The Chan Zuckerberg Initiative (CZI) has awarded a grant to the lab of Gioele La Manno, together with the Karolinska Institute and The University of Edinburgh. The collaborative research aims at new therapies for multiple sclerosis, and will be part of the Human Cell Atlas project.

Meet (me) the first ELISIR Fellow

I have been appointed the first Scholar of the EPFL Life Sciences Early Independence Research program (ELSIR), a revolutionary fellowship that gives talented PhD graduates the kind of research independence they could usually only get much later in their career.

New method reveals cell development

Researchers at Karolinska Institutet and Harvard Medical School report in the journal Nature that they have developed a technique for capturing dynamic processes in individual cells. Apart from studying disease processes, the method can be used to observe in detail how specialised cells are formed during embryonic development.

Midbrain study gives boost to Parkinson’s research

Two research teams at Karolinska Institutet have identified the dopamine-producing cells in the midbrain of mice and humans. They have also developed a method of assessing the quality of in-vitro cultured dopamine-producing cells, which can be of great benefit to research on Parkinson’s disease. The results are published in the academic journal Cell.

Special nerve cells cause goose bumps and nipple erection

The sympathetic nerve system has long been thought to respond the same regardless of the physical or emotional stimulus triggering it. However, in a new study from Karolinska Institutet published in the journal Nature Neuroscience, scientists show that the system comprises different neurons that regulate specific physiological functions, such as erectile muscle control.

Conversion of brain cells offers hope for Parkinson’s patients

Researchers at Karolinska Institutet have made significant progress in the search for new treatments for Parkinson’s disease. By manipulating the gene expression of non-neuronal cells in the brain, they were able to produce new dopamine neurons. The study, performed on mice and human cells, is published in the prestigious scientific journal Nature Biotechnology.

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Our work on Tomographical reconstruction of sequencing based technologies is now on the biorxiv. Enjoy!


Dimitri Lallement joins the lab for a Masters thesis project. He is enrolled in the Computer Science Engineering program, ENSIMAG at Grenoble and doing a exchange with EPFL. He has studied his Bachelor at the University of Bordeaux and studied as Data Scientist Junior at CNES. He wants to face challenging research problem and explore new methods that can help the interpretation of single-cell RNAseq datasets. Welcome Dimitri!


Halima Schede joins the lab for a Masters project. She is enrolled in the Bioengineering program and has studied in biology and mathematics at McGill. With her passion for machine learning and neural networks and her knowledge of anatomy and genetics she will turn a bunch of omics data in useful insights of the molecular anatomy of the brain. Welcome Halima!


Anurag Ranjak joins the lab for a Masters project. Anurag is a Chemical Engineer with industry experience in software engineering. He will adventure in spatial transcriptpomics and image reconstruction.He recently “converted” to biology and enrolled in EPFL Masters in Life Sciences. Welcome Anurag!


Our work on RNA velocity, the time derivative of gene expression, is now out in Nature. A lot of interesting new evidence and analysis added to the initial bioarxiv preprint. We put great attention to feature possibilities and the limits of the estimation approach. velocyto software is mature and ready to use. Enjoy!


Selected Publications

Here we show that RNA velocity - the time derivative of RNA abundance - can be estimated by distinguishing unspliced and spliced mRNAs in standard single-cell RNA sequencing protocols. RNA velocity is a vector that predicts the future state of individual cells on a timescale of hours.
Nature, 2018

We used RNA sequencing of half a million single cells to create a detailed census of cell types in the mouse nervous system. We mapped cell types spatially and derived a hierarchical, data-driven taxonomy.
Cell, 2018

We discover: Species differences in developmental timing and cell proliferation. Multiple radial glia subtypes biased toward distinct fates. Adult dopaminergic neuron subtypes emerge postnatally. A machine learning method to score dopaminergic differentiation of stem cells
Cell, 2016

We explored the heterogeneity of mouse stellate and thoracic ganglia and found an unexpected variety of cell types. We identified specialized populations of nipple- and pilo-erector muscle neurons. Our results provide compelling evidence for a highly sophisticated organization of the sympathetic nervous system into discrete outflow channels that project to well-defined target tissues and offer mechanistic insight into how diversity and connectivity are established during development.
Nature Neuroscience, 2016


. RNA velocity in single cells. Nature, 2018.

PDF Supplementary

. Molecular architecture of the mouse nervous system. Cell, 2018.

PDF Dataset Supplementary

. Spatial organization of the somatosensory cortex revealed by cyclic smFISH. Nature Methods, 2018.

PDF DataPage

. STRT-seq-2i: dual-index 5ʹ single cell and nucleus RNA-seq on an addressable microwell array. Scientific Reports, 2017.

PDF Supplementary

. Molecular analysis of the midbrain dopaminergic niche during neurogenesis. biorxiv, 2017.


. Induction of functional dopamine neurons from human astrocytes in vitro and mouse astrocytes in a Parkinson's disease model. Nature Biotechnology, 2017.


. Molecular diversity of midbrain development in mouse, human, and stem cells. Cell, 2016.

PDF Supplementary Data visualizations

. Visceral motor neuron diversity delineates a cellular basis for nipple-and pilo-erection muscle control. Nature Neuroscience, 2016.

PDF Supplementary

. Single-cell transcriptomics reveals that differentiation and spatial signatures shape epidermal and hair follicle heterogeneity. Cell Systems, 2016.


. Oligodendrocyte heterogeneity in the mouse juvenile and adult central nervous system. Science, 2016.

PDF Supplementary

. Cell types in the mouse cortex and hippocampus revealed by single-cell RNA-seq. Science, 2015.

PDF Supplementary

. Quantitative single-cell RNA-seq with unique molecular identifiers. Nature methods, 2014.

PDF Supplementary


Below the scientific software I have been working on:


A package for the analysis of expression dynamics in single cell RNA seq data. For more information go to the velocyto homepage


A tool for building analysis pipeline for big single cell RNA sequencing projects


Core implementation the standard format to store and work with single cell expression data. For more information go to the loompy homepage


Negative binomial generalized linear model for single cell expression data


An alternative, lightweight, python interface to the Bayesian Modeling language Stan.


Reference implementation of the clustering algorithm described in Zeisel et al. 2015


An older file format designed to store smaller single-cell RNA seq datasets