I just made a new website for my lab: ishaquelab.github.io. With the help of Claude it was shockingly fast to make!

The OpenProblems.bio team will be the driving force behind "SpaceHack 5.0: Multi-Modal Spatial Benchmarking and FAIR Data Standards". We'll be covering spatial omics, foundation models, data archive and lots more. Details: www.denbi.de/de-nbi-event... Registration: www.denbi.de/helpdesk?opt...

I am thrilled to share that today I was promoted to Professor of Cancer Bioinformatics at @bihatcharite.bsky.social! It's been an emotional day reflecting on everyone who dedicated their time, energy, and trust in me. So much to be grateful for, and so much excitement for the adventures ahead.

Single-nucleus transcriptomics of large-cell pancreatic neuroendocrine carcinoma uncovers aberrant brain-type neuronal programs and stress-responsive cell states, revealing therapeutic vulnerabilities for this aggressive cancer. PDF available: www.nature.com/articles/s42...

Very happy to see our newest (non-)benchmark study up on @natmethods.nature.com: doi.org/10.1038/s415.... Its started with the SpaceHack 2.0 hackathon back in 2023, where we wanted to benchmark methods for spatial clustering/niche/domain detection. Turns out this is very hard to do well...

Beyond benchmarking: an expert-guided consensus approach to spatially aware clustering - Nature Methods

Benchmarking spatially aware clustering is challenging. SACCELERATOR is an open-source, extensible framework that formalizes expert-guided spatial clustering analysis.

doi.org

Are you annoyed that you paid for 2um resolution in your VisiumHD experiment, but have to bin to 8um? Try out Saisnc, our cell-segmentation free tool that enables cell typing at 2 um resolution: sainsc.readthedocs.io/stable/index.... I dont think anything else can do the same...

Naming tools is an art, and when it goes right it feels epic... until everyone pronounces the name wrong! Our cell-segmentation free too SAINSC was supposed to be pronounced "science", but no one managed to get it right. So, naturally, we improved documentation on RTD: sainsc.readthedocs.io/latest/

Cell segmentation for spatial transcriptomics isn’t so easy, right? We thought so too. A wonderful group lead by @garybader.bsky.social and @rgottardo.bsky.social put together a perspectives piece on where things stand, the challenges, and what’s next. Check it out: arxiv.org/pdf/2606.09675

Excited to present at the 2nd edition of the Spatial Omics conference at @viblifesciences.bsky.social. I will talk about the challenges in benchmarking spatial clustering tools, major hurdles and way forward. Register here: vibbio.tech/SpatialOmics26 (early bird deadline of 11 May).

Ahead of International Women’s Day, check out this collection on the rewards and challenges that face women in science, including news and research covering fresh approaches to women’s health, the motherhood penalty, and more. go.nature.com/3OKCfhE

International Women’s Day

On Sunday 8 March, the world celebrates the achievements and well-being of its 4 billion female inhabitants.

go.nature.com

Check out our new preprint describing the extensions to SpatialLeiden clustering: - it's atlas scale (supporting intergration, and fast) - it's 3D ready (it accepts connections over serial sections) - it's multiomic ready (it accepts multiple omics layers) www.biorxiv.org/content/10.6...

Have you heard of @elixir-europe.org? It's a life sciences research infrastructure, bringing together #bioinformatics resources across Europe to store, analyse, share and reuse data. They are behind UniProt, ChEMBL, PDBe, ENA, bio.tools,... Read more here: f1000research.com/articles/14-....

F1000Research Article: Fostering and sustaining collaborative innovation: Insights from ELIXIR Europe's life science Communities.

Read the latest article version by Clare Garrard, Katharina F Heil, Maria Cristina Aspromonte, Bérénice Batut, Magda Chegkazi, John M Hancock, Elaine Harrison, Naveed Ishaque, Giselle Ke...

f1000research.com

Due to popular demand, we just extended documentation of SpatialLeiden to include guides for multi-sample, 3D and multi-omics spatial clustering: spatialleiden.readthedocs.io/latest/guide.... It's still remains as fast and intuitive as standard Leiden clustering. A preprint is on the way...

Our manuscript describing how cell overlaps in tissues sections affects spatial transcriptomics is now live on Nature Biotechnology: www.nature.com/articles/s41.... With it be provide the ovrlpy python tool to identify signals of overlapping cells in tissues, and assigning overlap scores to cells.

Identifying 3D signal overlaps in spatial transcriptomics data with ovrlpy - Nature Biotechnology

Ovrlpy identifies overlapping cell signals in the vertical dimension of spatial transcriptomics data.

nature.com

Spatial transcriptomics - helping authors wow reviewers with pretty pictures (... and interesting spatial biology).. and making it possible for bioinformaticians to submit journal cover art! Our Sainsc tool is featured as the back cover for Small Methods: onlinelibrary.wiley.com/doi/10.1002/...

Sainsc: A Computational Tool for Segmentation‐Free Analysis of In Situ Capture Data (Small Methods 5/2025)

Segmentation-Free Analyses Sainsc: a new tool for efficient whole organism spatial transcriptomics data analysis at the nanometre scale. Shown is a blended composite spatial map of total gene express...

onlinelibrary.wiley.com

Did you ever notice discrepancies in benchmarking of bioinformatics tools? We did too! Setting out to benchmark spatial clustering methods, we encountered major reproducibility issues in previous benchmarks and questionable "ground truths". More in our preprint: www.biorxiv.org/content/10.1...

Beyond benchmarking: an expert-guided consensus approach to spatially aware clustering

Spatial omics technologies have revolutionized the study of tissue architecture and cellular heterogeneity by integrating molecular profiles with spatial localization. In spatially resolved transcript...

biorxiv.org

Accurate cell segmentation remains a major issue for spatial transcriptomics. Elyas Heidari and colleagues from the Gerstung, Pe'er and Stegle Labs released Segger, a new algorithm that uses GNN to model both transcripts and cells. More details in their preprint: www.biorxiv.org/content/10.1...

Segger: Fast and accurate cell segmentation of imaging-based spatial transcriptomics data

The accurate assignment of transcripts to their cells of origin remains the Achilles heel of imaging-based spatial transcriptomics, despite being critical for nearly all downstream analyses. Current c...

biorxiv.org

🧬If you work with @10xgenomics.bsky.social Xenium, this might be of your interest. Our new study on Xenium exploration best practice and comparing it with other commercial platforms is now out in @naturemethods.bsky.social www.nature.com/articles/s41...

Optimizing Xenium In Situ data utility by quality assessment and best-practice analysis workflows - Nature Methods

This study presents a comprehensive evaluation of Xenium In Situ datasets and provides recommendations on analysis workflows.

nature.com

Have you been bothered that practically every #SpatialTranscriptomic analysis tool assumes data to be 2D? Well, you were right - overlapping cells are a really big problem. Check out our report on bioRxiv: 2D, or not 2D? Investigating Vertical Signal Integrity of Tissue Slices. t.ly/CQX8K

2D, or not 2D? Investigating Vertical Signal Integrity of Tissue Slices

Imaging-based spatially resolved transcriptomics can localise transcripts within cells in 3D. Cell segmentation precedes assignment of transcripts to cells and annotation of cell function. However, ce...

t.ly

SpatialLeiden is out in #GenomeBiology: t.ly/WQppF. It models both gene expression and spatial information for clustering. This allows you to perform e.g. spatially aware cell typing or domain identification. It's fast, scalable and intuitive for single-cell researchers. Try it out!

SpatialLeiden: spatially aware Leiden clustering - Genome Biology

Clustering can identify the natural structure that is inherent to measured data. For single-cell omics, clustering finds cells with similar molecular phenotype after which cell types are annotated. Le...

t.ly

Do you also think that #SpatialTranstriptomics and #AI will give rise to #DigitalPathology 2.0? We have an open PhD position for the HISTOMAP (Histology-based Molecular Analysis Platform) project to accelerate biomarker detection. Please apply here: www.bihealth.org/en/notices/b.... Spread the word!

BIH PhD Program - Call for PhD candidates 2025 - News - BIH at Charité

The BIH PhD program aims to promote interdisciplinarity and support young translational talents. The program co-funds PhD positions for excellent translational projects that fit one of the four BIH re...

bihealth.org

I tried Sainsc for our MERSCOPE data and Naveed, it works wonderfully! Importantly, the documentation is excellent. Thank you so much for the clear tutorial and explanations. This is truly a life saver for my analysis at the moment. Props to the team, this is awesome work!

Everyone knows by now that 42 is the answer to the ultimate question of life, the universe, and everything. But as I turn 42 today, I’ve realised something profound: it’s not the answer that matters - it’s the prompt!

Hello world. Our lab has a new home here on Bluesky! We will post about spatial omics, science, nice papers and lab activities. The account will be collectively managed by lab members. Happy spatial-omics everyone!

a cartoon of a man looking out a window at the stars

ALT: a cartoon of a man looking out a window at the stars

media.tenor.com

The calm before the storm... #SpaceHack starts tomorrow! Looking forward to 3 intense days of addressing unsolved data analysis problems for #SpatialTranscriptomics. More here: spatialhackathon.github.io

Try out SpatialLeiden for identifying spatial domains/clusters in your #SpatialTranscriptomics data: www.biorxiv.org/content/10.1... github.com/HiDiHlabs/sp... It's as easy as Leiden, but as performant as the best in class. Give it a try and let us know if it works for you!

SpatialLeiden - Spatially-aware Leiden clustering

Clustering can identify the natural structure that is inherent to measured data. For single-cell omics, clustering finds cells with similar molecular phenotype after which cell types are annotated. Le...

biorxiv.org

@gestaltsp.bsky.social welcome to BlueSky! @jasmineplummer.bsky.social @ioavlachos.bsky.social

Check out our new tools for #SpatialTranscriptomics. It's called Sainsc: onlinelibrary.wiley.com/doi/10.1002/.... #Sainsc can map cell types in high resolution spatial transcriptomics data, without segmenting cells! It's light weight, fast, and easy to use: sainsc.readthedocs.io/tutorials/in...

Sainsc: A Computational Tool for Segmentation‐Free Analysis of In Situ Capture Data

Spatially resolved transcriptomics methods can now profile the entire transcriptome, at full organism scale with nanometre resolution. Analysis frameworks that can efficiently and intuitively process....

onlinelibrary.wiley.com

Whole-brain spatial transcriptional analysis at cellular resolution Incredible study - 3D single cell imaging of the entire mouse brain - also on the cover of this week's #Science 🧪🔬🤯 www.science.org/doi/10.1126/...