ABOVE: CLEANING UP RNA SEQ DATA: Computational methods help researchers reduce noise in the data generated during single-cell RNA sequencing.
© ISTOCK.COM, JXFZSY
The papers
G. Eraslan et al., “Single-cell RNA-seq denoising using a deep count autoencoder,” Nat Commun, 10:390, 2019.
M. Büttner et al., “A test metric for assessing single-cell RNA-seq batch correction,” Nat Methods, 16:43–49, 2019.
In the not-so-distant past, researchers had to pool thousands of cells together for bulk RNA sequencing, yielding an averaged snapshot of gene expression. But advances in technology and significant reductions in cost now enable scientists to sequence RNA from single cells, unleashing a flood of transcription data.
“It used to be that you had to wait for the biologists [to generate data for analysis], but now we are the slow guys,” says Fabian Theis, a computational biologist at Helmholtz Zentrum München in Germany. “There’s just so much data to analyze that we can’t ...
