scRNA-seq cell classification sounds straightforward until you actually try it. Sparse data. Thousands of genes. Millions of possible cell relationships. Most methods treat each cell as isolated. A new framework from Nanjing University flips that. 🧵 doi.org/10.1049/syb2... #ComputationalBiology

1/ Everyone's talking about AI in biology. But what does it actually look like when you apply Transformer models to scRNA-seq? A new survey in Briefings in Bioinformatics maps the whole landscape. Here's what's worth knowing. 🧵 doi.org/10.1093/bib/... #SingleCell #scRNAseq #Bioinformatics

1/ The average bioinformatics tool is obsolete before most labs finish validating it. This is not an exaggeration, and it has real consequences for the science being produced. 🧵 #Bioinformatics #Genomics

scRNA-seq tells you what genes each cell is expressing. What it doesn't tell you is how those cells are related SCITE-RNA (Zimmermann, Sun, Hård et al., Genome Biology 2026) reconstructs tumor cell phylogenies directly from RNA sequencing data 🧵 doi.org/10.1186/s130... #scRNAseq #Bioinformatics

Targeted RNA-seq panels only find what they are designed to look for. A new study of 301 acute leukemia patients asks what whole RNA-seq finds instead. Kim, Park, Min et al. | Cells 2026 🧵 www.mdpi.com/2073-4409/15... #RNAseq #Bioinformatics #Leukemia #Genomics

Anti-TNF therapy fails roughly half of IBD patients. A new Gastroenterology paper identifies a molecular subgroup who may be systematically less likely to respond, and points to exactly why. 🧬 doi.org/10.1053/j.ga... #Trinobia #Bioinformatics #IBD #CrohnsDisease

Most scRNA-seq QC still comes down to three metrics: mt%, gene count, UMIs. The problem: cardiomyocytes, neurons, malignant cells, and erythroid cells can fail those filters simply because that is their biology. scQCenrich (Commun Biol 2026) was built to fix this. #scRNAseq #SingleCell

Preserving cells before scRNA-seq sounds straightforward. But which method holds up across labs, technicians, and shipping? A new multisite ABRF study tested 10x FLEX, Honeycomb HIVE, and Parse Evercode across 9 core facilities. Thread 🧵 #scRNAseq #singlecell #bioinformatics

New benchmarking paper on ONT's dorado RNA modification models, and the headline number is uncomfortable: 50-100% false discovery rate on real biological samples, even after filtering. Here is what that means for your experiments. academic.oup.com/nar/article/... #Epitranscriptomics #Nanopore

High-throughput sequencing has lived in core facilities for a decade. VITARI might be the first serious attempt to move it to the bench. Element Bio just announced their new platform. Here's what matters for sc/spatial labs. #SingleCell #SpatialTranscriptomics #NGS #Genomics #Bioinformatics

Python is another essential programming language in Bioinformatics... Here are 10 free Python 🐍 and Bioinformatics 🧬related resources to help you learning and practicing Python A 🧵 #Python #pythonprogramming #Bioinformatics

Bladder tumors are often classified as one molecular subtype. A new spatial atlas shows that classification can break down at the level that matters most: where the cancer actually is. aacrjournals.org/cancerdiscov... #BladderCancer #Oncology

Adding experimental data made RNA structure predictions worse. Not because the chemistry was wrong. Because the signal alignment upstream was noisy. That is the problem segSHAPE was built to fix. www.biorxiv.org/content/10.6... #Trinobia #ComputationalBiology

A pan-cancer single-cell atlas of tumor-associated dendritic cells just published in Nature Communications. Built by VIB and VUB. 178,000+ cells. 14 mouse models. 10 human cancer types. 🧬 www.nature.com/articles/s41... #Trinobia #Bioinformatics #scRNAseq

If you are running DESeq2 on APA-seq data, you are using the wrong tool for the job. A new Briefings in Bioinformatics paper builds the right one. doi.org/10.1093/bib/... #Bioinformatics #RNAseq #Transcriptomics

1.1 million gut cells. 343 individuals. One of the largest single-cell atlases ever built for Crohn's disease. IBDverse is out in Nature Genetics, and the biology it surfaces is worth paying attention to. www.nature.com/articles/s41... #SingleCell #Bioinformatics #IBD

CRISPR screens tell you what genes matter. Spatial transcriptomics tells you where. Perturb-DBiT does both at once, in intact tissue, with 80,000+ guide libraries. Nature Biotechnology, June 2026. www.nature.com/articles/s41... #SpatialTranscriptomics #CRISPR #Bioinformatics

scRNA-seq loses cell morphology during dissociation. STAMP keeps it. A new mini review from St. Jude walks through the full downstream Python pipeline for STAMP data, linking gene expression directly to cell shape, size, and marker localization. 🧵 #SpatialTranscriptomics #Bioinformatics

You've run your scRNA-seq experiment. Now you want to know where your cells are heading. You reach for RNA velocity — but which method do you use, and does it actually matter? Turns out: yes, quite a lot. #RNAvelocity #scRNAseq #Bioinformatics #SingleCell #Genomics

Single LLMs can annotate cell types. They can also hallucinate them. 56% of initial predictions in a new study were classified as hallucinations. What if you make multiple LLMs deliberate until they agree? www.nature.com/articles/s42... #scRNAseq #Bioinformatics #LLM #AI

We just wrapped up a hands-on scRNA-seq data analysis workshop for PhD students at @dkfz.bsky.social 🎉 From experimental design to biological interpretation, researchers worked through the complete single-cell analysis journey. #scRNAseq #SingleCellRNAseq #Bioinformatics #ComputationalBiology

Most sequence-to-function models are trained on bulk tissue data. Decima changes that, trained on 22M+ single cells, it predicts gene expression from DNA sequence at cell type resolution. #Bioinformatics #scRNAseq #Genomics #MachineLearning #GeneRegulation

Learning R is an essential step for practicing bioinformatics. Here are 10 free resources to get you started 👇 #Rstats #Bioinformatics #Biology #Programming #Trinobia

1/7 Fungi kill ~1.7M people/year. They threaten enough crops to feed 4B people. Yet fungal infections remain one of the most underfunded areas in all of infectious disease biology. scRNA-seq is starting to change that. 🧵 #scRNAseq #FungalInfections

1/
Still a great intro to genomic surveillance:
 cambiotraining.github.io/sars-cov-2-g... #Trinobia #Bioinformatics #Genomics #NGS #GenomicSurveillance #Phylogenetics #Nextstrain #VariantCalling #ComputationalBiology #LifeSciences #Biotech #Research #Science #DataScience #MolecularBiology

Your RNA-seq differential expression results might be cleaner than you think. Or messier. The problem is you probably can't tell from the analysis alone. 🧵 Paper: academic.oup.com/bib/article/... #Bioinformatics #RNAseq #BatchEffects #DifferentialExpression #DeepLearning #ComputationalBiology

Single-cell clustering sounds straightforward until you actually try it. Dropout, technical noise, and sparsity mean clean cluster boundaries are often artifacts of how you looked at the data. Paper: academic.oup.com/bib/article/27/3/bbaf169/8698827 #scRNAseq #Bioinformatics #CellClustering

7 web tools to explore genomics data you should know 🧵 #Bioinformatics #Genomics

Most RNA splicing models tell you what a sequence does. A new model from UPenn tells you what sequence you need to get the splicing outcome you want. elifesciences.org/articles/106... #RNAsplicing #GenomicsAI #Trinobia

Your RNA-seq results look clean. The statistics check out. The volcano plots look great. And you might still be completely wrong about the biology. Here is why that happens, and what to do about it. #SpatialTranscriptomics #SingleCellRNAseq #PancreaticCancer #Bioinformatics

Bioinformatics vs Computational Biology. Are they really different? 🧬 Often used interchangeably. But they are not the same thing. A thread. 👇 #Bioinformatics #ComputationalBiology #DataScience #Genomics #LifeSciences #BiologyJobs #ScientificComputing #Biotech #STEM

Three things in bioinformatics worth knowing this week: 1)🛠 Tool of the week: TAP‑seq A new protocol paper. Designed for CRISPR screens where full RNA‑seq does not scale. Targets a gene panel to cut cost and increase sensitivity where signal matters. #Bioinformatics #RNAseq

1/ Sequencing the entire transcriptome for every perturbation is too expensive. This workflow offers a solution. 🧵 #Trinobia #Bioinformatics #scRNAseq #SingleCell #CRISPR #Genomics #Transcriptomics #RNAseq #FunctionalGenomics #PerturbSeq #TAPseq #NextGenSequencing #NGS #ComputationalBiology

Most RNA-seq workflows stop at “which genes are expressed.” That is only half the biology. The real question: which RNAs are interacting? 🧬 A new study maps one of the most comprehensive RNA interaction atlases to date. #RNAseq #Bioinformatics #Trinobia #Genomics #SystemsBiology #Transcriptomics

Most researchers do not struggle because there is not enough literature. They struggle because there is too much, and it grows every day. Here is what usually happens. #AI #MachineLearning #Research #Science #Biology #Medicine #Bioinformatics #SciComm #AcademicTwitter #PhDLife

🧬💻 Top 10 resources to learn Bioinformatics — 🧵⬇️ (DM us if you want the PDFs) #Bioinformatics #Genomics #ComputationalBiology #DataScience #Python #RStats #MachineLearning #Genetics #Bioinformatician #LearningResources

Most RNA-seq analyses stop at the gene level. That is a problem. Much of disease biology actually plays out one level down, at the isoform and splicing level. #RNAseq #Splicing #Isoforms #Genomics #Bioinformatics #ComputationalBiology #Transcriptomics #Research #DataScience #Trinobia

🧬 Git and GitHub are essential resources for bioinformaticians and programmers. Yet many people still don't fully understand the difference between them. Here's a quick summary of their key distinctions 👇 #Git #github #programming #Biology #Bioinformatics

One thing we kept noticing at the Trinobia workshops: people weren't confused by the biology. They were confused by the language. Bioinformatics jargon assumes too much. Here's a thread to unpack the terms that come up most. 🧵 #Trinobia #Bioinformatics #Research #ScienceCommunication #RNAseq

Immunotherapy can be life changing for some bladder cancer patients and completely ineffective for others. A new European Urology study uses integrated multi omics to explain the gap. 🧵 #BladderCancer #Immunotherapy #Oncology #MultiOmics #SingleCell #Bioinformatics #ComputationalBiology #Medicine

mRNA QC is finally evolving. Oxford Nanopore and Lonza just announced a GMP-ready direct RNA sequencing solution for full-length, native mRNA analysis. nanoporetech.com/news/lonza-a... #mRNA #GMP #QualityControl #Sequencing #Biopharma #Bioinformatics #RegulatoryScience #Genomics #RNAseq

Many times you end up with messy, inconsistent, and unorganized data 😖 If you want to avoid the cleaning headaches, the {janitor} R package by Sam Firke has simple functions for examining and cleaning dirty data🧹 #Bioinformatics #RStats #DataCleaning #DataScience #OpenSource #RNAseq #DataWrangling

If this feels familiar, you are not alone. The field moved fast. This thread explains why the field feels so hard to catch up with. 🧵 #Trinobia #Bioinformatics #Genomics #NGS #ComputationalBiology #Research #DataAnalysis #Statistics #LifeSciences #RNAseq #SingleCell #Academia

Which programming languages should you actually learn to start bioinformatics? 👇🧵 Not everything. Not all at once. Focus on what shows up in real analyses and papers. #Bioinformatics #ComputationalBiology #Genomics #LifeSciences #Research #Trinobia

Working with genomics, single cell data, or predictive models in biology? This Nature Methods paper belongs in your reading list. www.nature.com/articles/s41... #Trinobia #Bioinformatics #ComputationalBiology #Genomics #SingleCell #MachineLearning #Research #Biology #Medicine

Most RNA structure studies show you a crowd snapshot. sm‑PORE‑cupine lets you watch individuals. #RNAstructure #Nanopore #DirectRNASequencing #SingleMolecule #RNAseq #Bioinformatics #Genomics #Transcriptomics #ComputationalBiology #NatureMethods #Research #Biology #LifeSciences #Trinobia

Working all day with no fun? 😩🥱 Not anymore! 🎲🎯♟️ Take some time off coding and running scripts all day and try out this fun R package called Rcade It also contains my favourite game: Pacman 😄✌️ github.com/RLesur/Rcade #RStats #OpenSource #CodingFun #RProgramming #DataScience #Pacman

🔬 AI tools are changing how researchers communicate science. We’re moving beyond static PDFs. Now, you can turn a research paper into a video.

1/ Why does my code run perfectly, but the results make zero sense? 😅 #Bioinformatics #Research #DataScience #AIinScience #Genomics #RNAseq #ComputationalBiology #MachineLearning #Statistics #Reproducibility #OpenScience #Biology #Biotech #AcademicResearch #PhDLife #Science #AI

Most m6A pipelines skip the very controls that would tell us how many calls are wrong. That gap matters more than basecaller choice. New reviewed eLife preprint puts numbers under pressure. #m6A #Nanopore #Bioinformatics #RNAseq #Epitranscriptomics #Genomics #MethodsMatter