Show Notes
This release contains only the music track from Base by Base Episode 28.
Song title: Where the Signal Lives
Original Base by Base episode: 28: scPrediXcan: Deep learning meets single-cell TWAS
Article metadata:
Article title: scPrediXcan integrates deep learning methods and single-cell data into a cell-type-specific transcriptome-wide association study framework
Journal: Cell Genomics
DOI: 10.1016/j.xgen.2025.100875
Reference: Zhou Y., Adeluwa T., Zhu L., Salazar-Magaña S., Sumner S., Kim H., Gona S., Nyasimi F., Kulkarni R., Powell J.E., Madduri R., Liu B., Chen M., Im H.K. scPrediXcan integrates deep learning methods and single-cell data into a cell-type-specific transcriptome-wide association study framework. Cell Genomics. 2025;5:100875. doi:10.1016/j.xgen.2025.100875
Lyrics:
Verse 1
Midnight on a bright-lit screen, I watch the numbers breathe
Quiet cells in crowded graphs, hiding what we need
A thousand little switches, coded in a simple chain
But the story blurs in bulk, like thunder in the rain
Pre-Chorus
So we zoom in closer, frame by frame
Let each cell type say its name
Turn the noise into a map
Find the spark inside the gap
Chorus
Tell me where the signal lives, where the signal lives
In the beta and the beat, in the places data gives
From the sequence to the traits, we draw the bridge we need
One genome, many voices—now we hear them lead
Verse 2
Deep lines read the letters, guess the patterns they imply
Epigenome in the shadows, like a pulse behind the eye
Then we make it run in straight lines, so the summary can sing
SNP by SNP it locks in time, a tighter reasoning
Bridge
Not every arrow points the right way, sometimes signs reverse
Promoters aren’t the whole wide world, enhancers still disperse
But when we stack the evidence and let the p-values align
The candidates step forward, clear in context, cell by cell, in kind
Final Chorus
Tell me where the signal lives, where the signal lives
In islets, in immune fire, in the differences it gives
From the sequence to the traits, we draw the bridge we need
One genome, many voices—now we hear them lead
