Code and results from TotalSeqC antibody titration and pipeline benchmarking for CITE-seq experiments.
Data and Seurat V3 objects from the study is deposited at FigShare under this DOI: 10.6084/m9.figshare.c.5018987
This repository contains all the code used in the processing of the aligned data and data analysis (used for generating all figures) included in the manuscript at BioRxiv.org:
Manuscript
Improving oligo-conjugated antibody signal in multimodal single-cell analysis. Terkild Brink Buus, Alberto Herrera, Ellie Ivanova, Eleni Mimitou, Anthony Cheng, Thales Papagiannakopoulos, Peter Smibert, Niels Odum, Sergei B Koralov. bioRxiv 2020.06.15.153080; doi: https://doi.org/10.1101/2020.06.15.153080
Pre-processing:
- Loading data, Demultiplexing, Preprocessing and down-sampling - Supplementary Figure S1
- Load unfiltered data and determine cell-containing vs. empty droplets - Supplementary Figure S6
Data analysis:
- Antibody concentration titration - Figure 1, 2 and Supplementary Figure S2
- Reducing staining volume - Figure 3 and Supplementary Figure S3
- Reducing cell number at staining - Figure 4 and Supplementary Figure S4
- Reducing cell number mitigates reduced staining volume - Supplementary Figure S5
- ADT signal in cell-containing vs. empty droplets - Figure 5 and Supplementary Figure S8
- 10X Datasets: UMI per marker plots - Supplementary Figure S7
- Comparison of ADT counting methods - Figure 6 and Supplementary Figure S9
We also included the Snakefiles used with Snakemake to generate the alignment and counting data from our dataset and for the 10X datasets.