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mouse_organogenesis-m-om

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# Decoding gene regulation in the mouse embryo using single-cell multi-omics

This repository contains the scripts to reproduce the results of the manuscript [Decoding gene regulation in the mouse embryo using single-cell multi-omics](https://www.biorxiv.org/content/10.1101/2022.06.15.496239v1). 


Abstract
--------
Following gastrulation, the three primary germ layers develop into the major organs in a process known as organogenesis. Single-cell RNA sequencing has enabled the profiling of the gene expression dynamics of these cell fate decisions, yet a comprehensive map of the interplay between transcription factors and cis-regulatory elements is lacking, as are the underlying gene regulatory networks. Here we generate a multi-omics atlas of mouse early organogenesis by simultaneously profiling gene expression and chromatin accessibility from tens of thousands of single cells. We develop a computational method to leverage the multi-modal readouts to predict transcription factor binding events in cis-regulatory elements, which we then use to infer gene regulatory networks that underpin lineage commitment events. Finally we show that these models can be used to generate in silico predictions of the effect of transcription factor perturbations. We validate this experimentally by showing that Brachyury is essential for the differentiation of neuromesodermal progenitors to somitic mesoderm fate by priming cis-regulatory elements.

<p align="center"> 
<img src="https://easymed.ai/models/AlyssaS/mouse_organogenesis-m-om/git/ci/main/tree/images/overview_github.png?raw=true" width="900" height="400"/>
</p>


Content
-------
* `/acc/`: analysis of chromatin accessibility data
* `/rna/`: analysis of RNA expression data
* `/accrna/`: simultaneous analysis of RNA expression and chromatin accessibility data

Snakemake pipeline
-------
We provide snakemake pipelines that can be used to reproduce many results. 
* `/rna/snakemake`: snakemake pipeline for RNA expression
* `/atac/ArchR/snakemake`: snakemake pipeline for chromatin accessibility using ArchR
* `/rna_atac/snakemake`: snakemake pipeline to integrate RNA expression and chromatin accessibility results (MOFA, in silico ChIP-seq, etc.)

Please note that the snakemake pipeline is rather complex and needs to be simplified and polished. It is currently useful to get an idea of the pipeline, but bare in mind that it  won't work straight away.

IGV Genome browser session
-------
We provide a precomputed IGV Genome Browser Session that can be used to interactively explore the ATAC-seq profiles, as shown in the screenshot below:

<p align="center"> 
<img src="images/igv_screenshot_github.png" width="650" height="350"/>
</p>

It can be downloaded running the following command line:
```
wget ftp://ftpusr92:5FqIACU9@ftp1.babraham.ac.uk/igv_session_celltype.tar.gz
```

Then load the file `igv_session.xml` using `File -> Open Session`.

<!-- The following [videotutorial](XXX) shows how to download and load the IGV session -->

R Shiny app
-------
The R shiny app for interactive data analaysis is available [here](https://www.bioinformatics.babraham.ac.uk/shiny/shiny_multiome_organogenesis/)

<!-- Pre-recorded talk
-------
This precorded talk by Ricard Argelaguet presents an overview of the study. -->

Directories
-------
* Mapping to the reference atlas: `/rna/mapping`
* MOFA dimensionality reduction: `/rna_atac/mofa`
* Analysis of gene markers: `/rna_atac/rna_vs_acc/pseudobulk/gene_markers_rna_vs_acc`
* in silico ChIP-seq: `/rna_atac/virtual_chipseq_library`
* Metacell inference: `/rna/metacells/run`
* Catalogue of TF activities per cell type (Figure 3): `/rna_atac/rna_vs_chromvar_chip/pseudobulk/per_celltype`
* Gene regulatory network of NMP differentiation (Figure 4): `/rna_atac/gene_regulatory_networks/metacells/trajectories`

Data
----
<!-- The raw data is accessible at GEO ([XXXX](XXXX)).  -->
The data can be downloaded from the following FTP server: 
```
Hostname    ftp1.babraham.ac.uk
Username    ftpusr92
Password    5FqIACU9
FTP URL     ftp://ftpusr92:5FqIACU9@ftp1.babraham.ac.uk
```

Directory structure:

- `sample_metadata.txt.gz`: cell metadata file
- `results`: results folder
    - `rna`: results based on RNA expression alone
    - `atac`: results based on chromatin accessibility alone
    - `rna_atac`: results based on both RNA expression and chromatin accessibility
- `data`: data folder
    - `original`: CellRanger output files
    - `processed`: processed data objects
        - `rna`: Seurat, anndata and SingleCellExperiment objects.
        - `atac/archR`: ArchR objects
- `igv_session_celltype.tar.gz`: IGV session of celltype-specific ATAC profiles
- `igv_session_brachyury_ko.tar.gz`: IGV session of celltype-specific ATAC profiles for the Brachyury KO study

To download a specific file:
```
wget ftp://ftpusr92:5FqIACU9@ftp1.babraham.ac.uk/data/processed/rna/SingleCellExperiment.rds .
```

To download everything (~60GB):
```
wget -r ftp://ftpusr92:5FqIACU9@ftp1.babraham.ac.uk/ .
```

If your download from the FTP server is slow, we also provide a temporary download via Dropbox [here](https://www.dropbox.com/sh/y4drtqi82vwl8vf/AAAsLcrye8jUTm1XPv7VNYhFa?dl=0)


Twitter thread
--------
We all know this is the most important day in the road towards a scientific publication:  

[![Twitter URL](https://img.shields.io/twitter/url/https/twitter.com/bukotsunikki.svg?style=social)](https://twitter.com/RArgelaguet/status/1537146799772815366)

Contact
-------
We have created a Slack group to discuss results, questions, collaborations, etc. related to the study. Feel free to drop by [using this link](https://join.slack.com/t/mouseembryo10-waq1273/shared_invite/zt-1dxn064kk-garRxOLAhLOUFNZBwqzfqQ). Alternatively, feel free to reach me via email at rargelaguet@altoslabs.com


	a/README.md		b/README.md
1	# Decoding gene regulation in the mouse embryo using single-cell multi-omics	1	# Decoding gene regulation in the mouse embryo using single-cell multi-omics
2		2
3	This repository contains the scripts to reproduce the results of the manuscript [Decoding gene regulation in the mouse embryo using single-cell multi-omics](https://www.biorxiv.org/content/10.1101/2022.06.15.496239v1).	3	This repository contains the scripts to reproduce the results of the manuscript [Decoding gene regulation in the mouse embryo using single-cell multi-omics](https://www.biorxiv.org/content/10.1101/2022.06.15.496239v1).
4		4
5		5
6	Abstract	6	Abstract
7	--------	7	--------
8	Following gastrulation, the three primary germ layers develop into the major organs in a process known as organogenesis. Single-cell RNA sequencing has enabled the profiling of the gene expression dynamics of these cell fate decisions, yet a comprehensive map of the interplay between transcription factors and cis-regulatory elements is lacking, as are the underlying gene regulatory networks. Here we generate a multi-omics atlas of mouse early organogenesis by simultaneously profiling gene expression and chromatin accessibility from tens of thousands of single cells. We develop a computational method to leverage the multi-modal readouts to predict transcription factor binding events in cis-regulatory elements, which we then use to infer gene regulatory networks that underpin lineage commitment events. Finally we show that these models can be used to generate in silico predictions of the effect of transcription factor perturbations. We validate this experimentally by showing that Brachyury is essential for the differentiation of neuromesodermal progenitors to somitic mesoderm fate by priming cis-regulatory elements.	8	Following gastrulation, the three primary germ layers develop into the major organs in a process known as organogenesis. Single-cell RNA sequencing has enabled the profiling of the gene expression dynamics of these cell fate decisions, yet a comprehensive map of the interplay between transcription factors and cis-regulatory elements is lacking, as are the underlying gene regulatory networks. Here we generate a multi-omics atlas of mouse early organogenesis by simultaneously profiling gene expression and chromatin accessibility from tens of thousands of single cells. We develop a computational method to leverage the multi-modal readouts to predict transcription factor binding events in cis-regulatory elements, which we then use to infer gene regulatory networks that underpin lineage commitment events. Finally we show that these models can be used to generate in silico predictions of the effect of transcription factor perturbations. We validate this experimentally by showing that Brachyury is essential for the differentiation of neuromesodermal progenitors to somitic mesoderm fate by priming cis-regulatory elements.
9		9
10	<p align="center">	10	<p align="center">
11	<img src="images/overview_github.png" width="900" height="400"/>	11	<img src="https://easymed.ai/models/AlyssaS/mouse_organogenesis-m-om/git/ci/main/tree/images/overview_github.png?raw=true" width="900" height="400"/>
12	</p>	12	</p>
13		13
14		14
15	Content	15	Content
16	-------	16	-------
17	* `/acc/`: analysis of chromatin accessibility data	17	* `/acc/`: analysis of chromatin accessibility data
18	* `/rna/`: analysis of RNA expression data	18	* `/rna/`: analysis of RNA expression data
19	* `/accrna/`: simultaneous analysis of RNA expression and chromatin accessibility data	19	* `/accrna/`: simultaneous analysis of RNA expression and chromatin accessibility data
20		20
21	Snakemake pipeline	21	Snakemake pipeline
22	-------	22	-------
23	We provide snakemake pipelines that can be used to reproduce many results.	23	We provide snakemake pipelines that can be used to reproduce many results.
24	* `/rna/snakemake`: snakemake pipeline for RNA expression	24	* `/rna/snakemake`: snakemake pipeline for RNA expression
25	* `/atac/ArchR/snakemake`: snakemake pipeline for chromatin accessibility using ArchR	25	* `/atac/ArchR/snakemake`: snakemake pipeline for chromatin accessibility using ArchR
26	* `/rna_atac/snakemake`: snakemake pipeline to integrate RNA expression and chromatin accessibility results (MOFA, in silico ChIP-seq, etc.)	26	* `/rna_atac/snakemake`: snakemake pipeline to integrate RNA expression and chromatin accessibility results (MOFA, in silico ChIP-seq, etc.)
27		27
28	Please note that the snakemake pipeline is rather complex and needs to be simplified and polished. It is currently useful to get an idea of the pipeline, but bare in mind that it won't work straight away.	28	Please note that the snakemake pipeline is rather complex and needs to be simplified and polished. It is currently useful to get an idea of the pipeline, but bare in mind that it won't work straight away.
29		29
30	IGV Genome browser session	30	IGV Genome browser session
31	-------	31	-------
32	We provide a precomputed IGV Genome Browser Session that can be used to interactively explore the ATAC-seq profiles, as shown in the screenshot below:	32	We provide a precomputed IGV Genome Browser Session that can be used to interactively explore the ATAC-seq profiles, as shown in the screenshot below:
33		33
34	<p align="center">	34	<p align="center">
35	<img src="images/igv_screenshot_github.png" width="650" height="350"/>	35	<img src="images/igv_screenshot_github.png" width="650" height="350"/>
36	</p>	36	</p>
37		37
38	It can be downloaded running the following command line:	38	It can be downloaded running the following command line:
39	```	39	```
40	wget ftp://ftpusr92:5FqIACU9@ftp1.babraham.ac.uk/igv_session_celltype.tar.gz	40	wget ftp://ftpusr92:5FqIACU9@ftp1.babraham.ac.uk/igv_session_celltype.tar.gz
41	```	41	```
42		42
43	Then load the file `igv_session.xml` using `File -> Open Session`.	43	Then load the file `igv_session.xml` using `File -> Open Session`.
44		44
45	<!-- The following [videotutorial](XXX) shows how to download and load the IGV session -->	45	<!-- The following [videotutorial](XXX) shows how to download and load the IGV session -->
46		46
47	R Shiny app	47	R Shiny app
48	-------	48	-------
49	The R shiny app for interactive data analaysis is available [here](https://www.bioinformatics.babraham.ac.uk/shiny/shiny_multiome_organogenesis/)	49	The R shiny app for interactive data analaysis is available [here](https://www.bioinformatics.babraham.ac.uk/shiny/shiny_multiome_organogenesis/)
50		50
51	<!-- Pre-recorded talk	51	<!-- Pre-recorded talk
52	-------	52	-------
53	This precorded talk by Ricard Argelaguet presents an overview of the study. -->	53	This precorded talk by Ricard Argelaguet presents an overview of the study. -->
54		54
55	Directories	55	Directories
56	-------	56	-------
57	* Mapping to the reference atlas: `/rna/mapping`	57	* Mapping to the reference atlas: `/rna/mapping`
58	* MOFA dimensionality reduction: `/rna_atac/mofa`	58	* MOFA dimensionality reduction: `/rna_atac/mofa`
59	* Analysis of gene markers: `/rna_atac/rna_vs_acc/pseudobulk/gene_markers_rna_vs_acc`	59	* Analysis of gene markers: `/rna_atac/rna_vs_acc/pseudobulk/gene_markers_rna_vs_acc`
60	* in silico ChIP-seq: `/rna_atac/virtual_chipseq_library`	60	* in silico ChIP-seq: `/rna_atac/virtual_chipseq_library`
61	* Metacell inference: `/rna/metacells/run`	61	* Metacell inference: `/rna/metacells/run`
62	* Catalogue of TF activities per cell type (Figure 3): `/rna_atac/rna_vs_chromvar_chip/pseudobulk/per_celltype`	62	* Catalogue of TF activities per cell type (Figure 3): `/rna_atac/rna_vs_chromvar_chip/pseudobulk/per_celltype`
63	* Gene regulatory network of NMP differentiation (Figure 4): `/rna_atac/gene_regulatory_networks/metacells/trajectories`	63	* Gene regulatory network of NMP differentiation (Figure 4): `/rna_atac/gene_regulatory_networks/metacells/trajectories`
64		64
65	Data	65	Data
66	----	66	----
67	<!-- The raw data is accessible at GEO ([XXXX](XXXX)). -->	67	<!-- The raw data is accessible at GEO ([XXXX](XXXX)). -->
68	The data can be downloaded from the following FTP server:	68	The data can be downloaded from the following FTP server:
69	```	69	```
70	Hostname ftp1.babraham.ac.uk	70	Hostname ftp1.babraham.ac.uk
71	Username ftpusr92	71	Username ftpusr92
72	Password 5FqIACU9	72	Password 5FqIACU9
73	FTP URL ftp://ftpusr92:5FqIACU9@ftp1.babraham.ac.uk	73	FTP URL ftp://ftpusr92:5FqIACU9@ftp1.babraham.ac.uk
74	```	74	```
75		75
76	Directory structure:	76	Directory structure:
77		77
78	- `sample_metadata.txt.gz`: cell metadata file	78	- `sample_metadata.txt.gz`: cell metadata file
79	- `results`: results folder	79	- `results`: results folder
80	- `rna`: results based on RNA expression alone	80	- `rna`: results based on RNA expression alone
81	- `atac`: results based on chromatin accessibility alone	81	- `atac`: results based on chromatin accessibility alone
82	- `rna_atac`: results based on both RNA expression and chromatin accessibility	82	- `rna_atac`: results based on both RNA expression and chromatin accessibility
83	- `data`: data folder	83	- `data`: data folder
84	- `original`: CellRanger output files	84	- `original`: CellRanger output files
85	- `processed`: processed data objects	85	- `processed`: processed data objects
86	- `rna`: Seurat, anndata and SingleCellExperiment objects.	86	- `rna`: Seurat, anndata and SingleCellExperiment objects.
87	- `atac/archR`: ArchR objects	87	- `atac/archR`: ArchR objects
88	- `igv_session_celltype.tar.gz`: IGV session of celltype-specific ATAC profiles	88	- `igv_session_celltype.tar.gz`: IGV session of celltype-specific ATAC profiles
89	- `igv_session_brachyury_ko.tar.gz`: IGV session of celltype-specific ATAC profiles for the Brachyury KO study	89	- `igv_session_brachyury_ko.tar.gz`: IGV session of celltype-specific ATAC profiles for the Brachyury KO study
90		90
91	To download a specific file:	91	To download a specific file:
92	```	92	```
93	wget ftp://ftpusr92:5FqIACU9@ftp1.babraham.ac.uk/data/processed/rna/SingleCellExperiment.rds .	93	wget ftp://ftpusr92:5FqIACU9@ftp1.babraham.ac.uk/data/processed/rna/SingleCellExperiment.rds .
94	```	94	```
95		95
96	To download everything (~60GB):	96	To download everything (~60GB):
97	```	97	```
98	wget -r ftp://ftpusr92:5FqIACU9@ftp1.babraham.ac.uk/ .	98	wget -r ftp://ftpusr92:5FqIACU9@ftp1.babraham.ac.uk/ .
99	```	99	```
100		100
101	If your download from the FTP server is slow, we also provide a temporary download via Dropbox [here](https://www.dropbox.com/sh/y4drtqi82vwl8vf/AAAsLcrye8jUTm1XPv7VNYhFa?dl=0)	101	If your download from the FTP server is slow, we also provide a temporary download via Dropbox [here](https://www.dropbox.com/sh/y4drtqi82vwl8vf/AAAsLcrye8jUTm1XPv7VNYhFa?dl=0)
102		102
103		103
104	Twitter thread	104	Twitter thread
105	--------	105	--------
106	We all know this is the most important day in the road towards a scientific publication:	106	We all know this is the most important day in the road towards a scientific publication:
107		107
108	[![Twitter URL](https://img.shields.io/twitter/url/https/twitter.com/bukotsunikki.svg?style=social)](https://twitter.com/RArgelaguet/status/1537146799772815366)	108	[![Twitter URL](https://img.shields.io/twitter/url/https/twitter.com/bukotsunikki.svg?style=social)](https://twitter.com/RArgelaguet/status/1537146799772815366)
109		109
110	Contact	110	Contact
111	-------	111	-------
112	We have created a Slack group to discuss results, questions, collaborations, etc. related to the study. Feel free to drop by [using this link](https://join.slack.com/t/mouseembryo10-waq1273/shared_invite/zt-1dxn064kk-garRxOLAhLOUFNZBwqzfqQ). Alternatively, feel free to reach me via email at rargelaguet@altoslabs.com	112	We have created a Slack group to discuss results, questions, collaborations, etc. related to the study. Feel free to drop by [using this link](https://join.slack.com/t/mouseembryo10-waq1273/shared_invite/zt-1dxn064kk-garRxOLAhLOUFNZBwqzfqQ). Alternatively, feel free to reach me via email at rargelaguet@altoslabs.com
113		113