Single-Cell RNA-seq: Sorting through the noise
"We came to AnyHelix because our internal team was hitting a wall with some noisy single-cell RNA-seq data. To be honest, our initial clustering looked like a blob, and we couldn't isolate the rare progenitor population we were looking for. We'd already spent three weeks trying to optimize the filtering ourselves without much luck.
AnyHelix ended up customizing a trajectory analysis that finally separated those sub-clusters. They identified 4 distinct transitional cell states that we had missed. What I appreciated most wasn't just the figures, which were honestly better than what I usually see in many manuscripts, but that they gave us the full R environment. When our postdoc wanted to change the color palette for a presentation, the code actually worked on the first try."