New in EMBO Reports, led by Yea-Lih Lin (Pasero lab, IGH): without TREX1, mouse tumor cells accumulate short cytosolic DNA from active chromatin, boosting anti-tumor immunity. Gen2i analyzed the sequencing, keeping the 1 read in 5 not placed at one locus. doi.org/10.1038/s443...

Great discussions at the Young Scientists Cancer Congress (YS2C) Centre de Recherche en Cancérologie de Toulouse (CRCT) Our interface got very positive feedback: it saves hours when writing a scientific paper, even without any bioinformatics analysis.

Friendly thought for the #bioinfo crowd.

The scariest failure in our field is not the pipeline that crashes. It is the one that runs clean and hands you a gorgeous, wrong figure.

☝🏼 The biggest time sink in collaborative bioinformatics projects isn't the analysis.

It's the back and forth !

"Which version of the figure?" "Can you resend the parameters?" "Is this the latest pipeline?"...

Analysis done.
Results look great.
Paper submitted.
6 months later: reviewer asks to rerun with modified parameters.

How do you handle traceability in your lab? Genuinely curious what's working.

#Bioinformatics #ReproducibleResearch #AcademicLife

Analysis done.
Results look great.
Paper submitted.
6 months later: reviewer asks to rerun with modified parameters.

How do you handle traceability in your lab? Genuinely curious what's working.

#Bioinformatics #ReproducibleResearch #AcademicLife

Instead of juggling emails, Slack, and disjointed software, what if you could run your analysis, tag a colleague to comment on a specific figure, and build your publication panel, all in the exact same workspace?

Meet GeneSys ! A central hub for your entire workflow.

How does your team currently handle feedback and collaboration on ongoing analyses?

#Bioinformatics #ResearchTools #ScienceSky

Real talk: how FAIR are your pipelines actually?

If your postdoc left tomorrow, could someone else reproduce the analysis from scratch?

#FAIRdata #OpenScience #AcademicLife

Real talk: how FAIR are your pipelines actually?

If your postdoc left tomorrow, could someone else reproduce the analysis from scratch?

#FAIRdata #OpenScience #AcademicLife

The bioinformatics bottleneck isn't a skills gap. It's a dependency problem.

What's the waiting that costs you the most time?

Something we hear constantly from biologists:

"I have the hypothesis. I have the samples. I'm spending my week waiting for someone who knows how to debug the pipeline." Not a unique story. A structural one.

Something we hear constantly from biologists:

"I have the hypothesis. I have the samples. I'm spending my week waiting for someone who knows how to debug the pipeline." Not a unique story. A structural one.

Honest question for the bio-info community:

How many hours a week do you spend on bioinformatics tasks you didn't sign up for?

Debugging environments, waiting for an engineer, re-running pipelines that "worked last time"...

We're building to fix this.
Curious what your biggest friction point is.