Cell Ranger6.1, printed on 07/06/2022
The Chromium Next GEM Single Cell 3’ and 5' HT kits (referred to as high throughput or HT) are high throughput, cost-effective solutions for profiling gene expression at the single cell level. In combination with Feature Barcode technology the 3' and 5' HT assays also enable simultaneous cell surface protein detection and CRISPR profiling in single cells. The HT kits offer 16 channels per chip, and allow more cells to be recovered per channel compared to the standard assay and LT kits:
The Chromium X Series is the next generation of 10x Genomics instrumentation, purposefully designed to enable high-throughput experiments, offering a highly optimized approach to single cell studies. The Chromium X Series is one instrument, available in two firmware options (Chromium X and Chromium iX). All 10x Genomics single cell dual index assays are supported on Chromium X Series instruments, but the HT kits can only be run on the Chromium X, not iX.
Cell Ranger 6.1 or later is required to analyze HT data. After demultiplexing the BCL files with cellranger mkfastq, run cellranger count or cellranger multi on the FASTQ data to obtain output files. The pipeline should autodetect HT libraries for 3' CellPlex samples, in which case the chemistry tab in the web_summary.html will show
HT appended. One can also use the
chemistry=SC3Pv3HT option in the multi CSV file (this is only recommended if there is an error in automatic detection).
The Chromium X enables million-cell experiments to be run on a single HT chip. To aggregate data from multiple GEM wells requires running cellranger aggr on the
molecule_info.h5 files output by cellranger count or cellranger multi.
Cell Ranger processes HT libraries similarly to standard libraries except for minor adjustments to certain parameters in the cell calling algorithm. Starting with Cell Ranger 6.1, it is recommended to use the
--expect-cells option for all analyses.
Loupe Browser 6.0 or later is recommended for the analysis of datasets with over 100k cells, and performs well on HT datasets of over one million cells.