ImmGen at 15
Immunological Genome Project.
Nat Immunol. 2020 Jul;21(7):700-703.
July 2020: GENCODE update
ImmGen is updating the gene/transcript reference framework used to map and assign RNAseq data. Liang Yang has performed the herculean task of re-processing all existing ULI RNAseq data against GENCODE Version M25
, from the previously used M16. This update applies to data on the “RNAseq Skyline
”, "Population Comparison (RNASeq)
" and "MyGeneSet
" databrowser pages.
In addition, Gene tables for datasets deposited at NCBI’s Gene Expression Omnibus (GSE109125, GSE122108, GSE122597) have been updated to M25, as have the raw count numbers and normalized tables found on the ImmGen Dataset page
Please be aware of small discrepancies that may occur while comparing to previously downloaded data or figures. Changes are minimal for most genes, but M25 differs from M16 by introducing around 2400 new genes and 8000 new transcripts (for a total of 55401 total genes, of which 21859 are recognized as protein-coding). Many of them are microRNA precursors, others correspond to better distinguished members of gene families. The most significant “newcomers” are Vps28, Tmem179b
, and Itprip
(primarily expressed in Mast cells, Macrophages and Granulocytes, respectively).
June 2020: Flamboyant past
It is with mixed feelings that we announce the retirement
of our beloved ImmGen Flash interface
Over the years, Flash has jazzed up the ImmGen website, providing dynamic and colored displays to the early databrowsers. Flash is unfortunately being phased out. For those nostalgic ImmGen users, we have left a small taste of the good old Flash in the Constellation databrowser
, but this will also come to pass, alas...
April 2020: COVID-19
During the pandemic, Immgen programs are naturally slowed down.
To support COVID-19 research worldwide, we are re-deploying here
some of our visualization tools to display datasets related to SARS-CoV2, the pathology or the immune response it elicits.
December 2019 : ImmGen Annual Workshop
The Immunological Genome Project hosted its annual Workshop on Dec 6.
As usual, ImmGen Participants braved the Boston weather and came to meet new members, discuss recent findings and share their thoughts about the Consortium's possible future directions.
This year's T-shirt is sure to become a collector's item.
New ImmGen Enhancer networks databrowser to explore Open Chromatin Regions associated with a gene.
A series of new tools
, developed by Eunice Esomonu and Liang Yang are now available through the databrowser page.
This new online tool is an extension to the article “cis-Regulatory Atlas of the Mouse Immune System” published by Yoshida et al in the February issue of Cell, which describes a matched epigenome and transcriptome analysis in 86 primary cell-types spanning the mouse immune system.
This work resulted in the description of 512,595 Open Chromatin Regions accessible in one or more immune cell-types, and in strong predictions of the transcription factors likely (by presence of DNA motif and correlated expression) to control the activity of each OCR.
The Enhancer Networks portal supports the
exploration of OCR accessibility for a
particular gene using several paths:
1-The display of OCRs associated with
this gene with their chromosome location.
2-The visualization of OCR accessibility in
key immune cell-types.
3-Transcription factors predicted to bind
More features will be added in the future.
July 2019: ImmGen Computational Workshop:
Organized by Tal Shay and Sara Mostafavi, two days of exciting presentations on cutting edge approaches to understanding cells and their regulatory networks, brainstorming on how these could be applied to ImmGen data or questions, or how ImmGen could tailor some of its profiling to dovetail with computational needs.
June 2019: Population comparison: The RNAseq version is OUT!:
Thank you to the patient ImmGen user (you know who you are) who pushed us to move this upgrade up the priority list.
As previously, the “Population Comparison”
databrowser compares gene expression between cell-types and returns a table of the most differential genes. Can be used for a simple pairwise comparison (e.g
. Follicular B vs
GC B cells) or for comparison between groups of populations (e.g
all CD4+ T vs
all CD8+ T cells), and either the new RNAseq
or the older microarray data
can be consulted.