Understanding sequencing library structure is essential for accurate genomics data processing. seqspec provides a machine-readable specification that standardizes library descriptions, improving preprocessing, reproducibility, and assay comparisons.  Learn more: academic.oup.com/bioinformati...

IGVF is building resources to better understand how genomic variation influences genome function and human health through predictive modeling, functional characterization, mapping, networking, and shared data resources. Learn more about our initiative: www.igvf.org/about/

FastGxC is a tool for identifying context-specific genetic effects from single-cell and bulk RNA-seq data. By modeling repeated samples from the same individual, it improves detection power and remains robust even with missing data. Explore the tool: github.com/BalliuLab/Fa...

New preprint! 📢 PerturbPlan introduces an analytical framework for designing Perturb-seq and TAP-seq experiments, reducing power calculation runtimes by up to seven orders of magnitude and enabling interactive experimental design. www.biorxiv.org/content/10.6...

A recent preprint presents an MPRA framework that assays cis-regulatory elements alongside their target promoter, providing a functional map of 1,214 CYP3A4 regulatory variants and insights into gene regulation, drug response, and disease. Read more: www.biorxiv.org/content/10.6...

Explore the IGVF YouTube channel for workshop recordings, research presentations, consortium updates, and insights from scientists working to understand how genomic variation impacts genome function. www.youtube.com/@igvf

MPRA is an R package that provides tools for the differential analysis of Massively Parallel Reporter Assay (MPRA) data, helping researchers investigate regulatory element activity at scale. Explore MPRA: github.com/hansenlab/mpra

Looking for information on a gene, variant, or genomic region? The IGVF catalog brings together experimental data and computational predictions from the IGVF Consortium and other resources on a single searchable platform. catalog.igvf.org

Hear from Andreas Gschwind, PhD, as he highlights enhancer-gene mapping, CRISPR perturbation data, predictive models, and tools within the IGVF catalog.  youtu.be/jVxcwRXZYMc

How can researchers access and build on IGVF resources?  In this workshop presentation, Michael Love, PhD, highlights the IGVF data portal, catalog, APIs, and computational tools supporting reproducible functional genomics research. youtu.be/W6Mr7O7gUNY

IGVF has adopted seqspec, a machine-readable standard helping improve reproducibility, transparency, and interoperability across functional genomics datasets. Learn how seqspec is supporting scalable data sharing and QC across IGVF: igvf.org/news/seqspec/

Roulette is a basepair-resolution model for predicting germline de novo mutation rates across the human genome, helping uncover mechanisms that shape mutagenesis, including the impact of Polymerase III transcription.  Explore the tool: github.com/vseplyarskiy...

Hear from Karen Mohlke, PhD, as she introduces the IGVF Consortium and its efforts to build a functional genomics resource connecting genetic variation to genome function and disease.  Check out the full presentation: youtu.be/CbCILxe_eSI?...

Why build a comprehensive variant effects catalog? Katherine Degner, PhD, explains how a trusted, centralized resource can help researchers explore how genes impact different tissues and cell types, all in one place. ▶️ youtu.be/Iof2mfE6sRM

Saturation genome editing of BARD1 variants resolves 95% of variants of uncertain significance, linking functional effects to cancer risk with high accuracy (AUC=0.99). Uncover the science behind it: www.medrxiv.org/content/10.1...

New preprint: Transcription factor collaboration shapes CD8+T cell states. Large-scale TF screens and single-cell profiling map regulatory programs and interactions (including RUNX–KLF2) that inform T cell exhaustion and potential cell therapy strategies. Read more: www.biorxiv.org/content/10.6...

Follow IGVF on YouTube for Q&As, research highlights, and insights from across the consortium. Subscribe and tune in: www.youtube.com/@igvf

MPRAflow is a pipeline for analyzing MPRA sequencing data, generating count tables, linking variants to barcodes, and modeling variant effects from saturation mutagenesis experiments. Explore the tool: github.com/shendurelab/...

New research combines CRISPR activation, Perturb-seq, and in situ screening to uncover RNA-based mechanisms that enhance T cell–mediated killing of cancer and infected cells.  Read more: www.nature.com/articles/s41...

The IGVF Data Portal brings together datasets, tools, models, and protocols from across the consortium, from raw sequencing data to analyzed variant effects. Explore the resource: data.igvf.org

What’s one of the biggest challenges in genomics today? Lea Starita explains how variants of uncertain significance limit genetic medicine, and how IGVF is working to solve it using functional data and predictive models. ▶️ youtu.be/yEjEeIIkj9Q

Looking for IGVF across social media? Visit our Linktree to find all IGVF platforms in one place and stay up to date on the latest research, tools, and consortium updates.  linktr.ee/IGVFConsortium

New preprint: Neuron–astrocyte interactions reshape neuronal gene regulation. Co-culture and CRISPR screens reveal regulatory elements and TF networks that control neuronal maturation and link to schizophrenia and Alzheimer’s disease. Read more: www.biorxiv.org/content/10.6...

What makes the IGVF Catalog exciting? Michael Love, PhD, explains how it moves beyond genome annotation to map networks linking variants, regulatory elements, genes, and phenotypes, offering a new way to understand genome function. 🎬 youtu.be/oC7a_IJw9X8

The IGVF Mapping Working Group generates large-scale single-cell datasets, developing computational pipelines to help uncover how genetic variation influences human health and disease. Learn more about IGVF Working Groups: igvf.org/working-grou...

How do noncoding variants drive immune disease? Using large-scale Perturb-seq in primary human CD4+ T cells, researchers map the chain from variant → CRE → gene → regulatory network, linking risk loci to shared disease programs. Read the preprint: www.biorxiv.org/content/10.6...

Handling large-scale single-cell data requires efficient tools. 🛠️ anndata is a Python package designed for working with annotated data matrices, offering sparse data support, lazy operations, and integration with PyTorch. Learn more: github.com/scverse/annd...

What drives the science behind IGVF? In this IGVF Q&A, members share how the team is tackling long-standing genomics challenges and building a comprehensive catalog of variant effects to advance human health & research. Tune in: youtu.be/zPzGIjSQJ4U?...

A new preprint from IGVF introduces a scalable workflow to address variants of uncertain significance (VUS). Across 40 genes, the approach reclassified 75% of 16,115 VUS and preclassified >90K variants—moving clinical genomics forward. Read more:  www.biorxiv.org/content/10.6...

SIMBA enables joint embedding of cells and their defining features into a shared latent space. This attribute supports single-cell and multimodal analysis, batch correction, and multi-omic integration.  Learn more: simba-bio.readthedocs.io/en/latest/

IGGSy 2026 is coming! July 5 - 9, join researchers from around the world to explore genome graphs, pangenomics, and metagenomics, including a dedicated Human Pangenome Project session with keynotes from speakers of varied specializations. Registration open now! iggsy.org

Recent IGVF research benchmarks Perturb-seq in human stem cells, enabling scalable analysis of gene and enhancer function during differentiation and disease. Uncover the science behind it: www.cell.com/stem-cell-re...

How does IGVF research move us closer to understanding human health and disease? Charles Gersbach, PhD, explains how mapping the function of genetic variation is key to unlocking better treatments, from cancer and fibrosis to neurodegeneration and aging. ▶️ youtu.be/R6Q3yavjGDs

A recent preprint introduces MaveMD, a clinical interface for MaveDB that integrates MAVE data with ClinVar and ClinGen to support variant classification and reduce VUS uncertainty. Uncover the science behind it:  www.medrxiv.org/content/10.1...

Momentum and connections is exactly right! Excited to see the impact highlighted in the 2025 Annual Report. 👏🏼

Large-scale perturbation of transcription factors and enhancers reveals regulatory networks shaping human heart development and congenital heart disease.  A new reference map helps interpret CHD genes and variants.   Uncover the research behind it: www.biorxiv.org/content/10.6...

Understanding how genomic variation shapes disease opens the door to entirely new therapeutic strategies. Hear from Jesse Engreitz, PhD, and other IGVF members in the full Q&A. ▶️ youtu.be/zPzGIjSQJ4U

Cells sense matrix stiffness through mechanoenhancers, genomic elements that tune gene activity in response to mechanical signals. Editing these enhancers can reshape cell behavior, pointing to new therapeutic possibilities. Read more: www.science.org/doi/10.1126/...

Cheers to another year of discovery! 🎇 As we wrap up 2025 and look toward 2026, we’re excited to share voices from across IGVF. Tune in to our IGVF Q&A featuring consortium members reflecting on this year’s work and what’s ahead: youtu.be/zPzGIjSQJ4U

Monod is a Python package for single-cell RNA-seq that integrates nascent and mature RNA using biophysical models, revealing regulatory dynamics beyond average expression. Learn more: www.nature.com/articles/s41...

Kallisto utilizes pseudoalignment to quickly estimate transcript abundances from RNA-seq data and can handle tens of millions of reads in minutes, all while maintaining high accuracy. Explore the tool: github.com/pachterlab/k...

NEW from IGVF: our NAR paper highlighting the IGVF Catalog, an open resource for exploring how genomic variation impacts function. Use the resource, explore the data, and tell us what you think! academic.oup.com/nar/advance-...

We're proud to recognize this year’s IGVF Team Science Award winners, leaders and teams whose work strengthens the entire consortium. Congratulations to each of our award recipients 👏🏽

Feeling extra grateful this November for the IGVF community! Thank you for your collaboration, dedication, and the incredible work you do to advance our understanding of human health and disease.

IGVF @ CAGI7! This year’s meeting features several talks from IGVF members, all aligned with our efforts to link genomic variation to function. Keynote by Douglas Fowler (UW). Late registration ends Dec 1. genomeinterpretation.org/cagi7.html

Stoked to share our latest work entitled: “Large-scale discovery of neural enhancers for cis-regulation therapies” shorturl.at/H3Qww This is an enormous team effort that I had the honour of spearheading with Nick Page and Florence Chardon. Bluetorial below.

Incredible work from the IGVF community! A major step forward for scalable CRT discovery, and a significant contribution to understanding gene regulation in human neurons.

🔍 scE2G is a computational pipeline for predicting genome-wide enhancer–gene regulatory links using single-cell ATAC-seq or paired ATAC + RNA-seq (multiome) data. Learn more & access the tool here: github.com/EngreitzLab/...

From data to discovery, IGVF is working to understand how genomic variation influences genome function and phenotype. Learn more about our work at www.igvf.org

Wishing everyone a spook-tacular Halloween! 👻 Whether you’re celebrating or just enjoying a well-earned weekend, we hope it’s a wickedly wonderful one!