Tool: Hera-T: an efficient and accurate algorithm for quantifying single-cell UMI count data
gravatar for Jennifer Pham
15 months ago by
Jennifer Pham380
San Diego CA
Jennifer Pham380 wrote:

We are glad to introduce hera-T, a fast and accurate algorithm to quantify gene abundances from 10X-Chromium data with high rates of non-exonic reads, developed by BioTuring team.

hera-T devises a new strategy for aligning reads to both transcriptome and genome references that considerably reduces both the running time and memory consumption. For a single-cell data set with 49M reads, hera-T took only 1.75 minutes to process and consumed 8GB RAM. For a sample dataset of 11 billion reads (about 1.3 million cells), hera-T needs 24GB RAM and takes 4 hours to finish.

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The t-SNE plots from hera-T and CellRanger are almost indistinguishable. Minor differences come from some difficult splicing alignment scenarios (with short exons) that hera-T addresses but Cell Ranger fails to address. ( enter image description here

Please find some initial benchmarks of hera-T here.

hera-T source code is available at under BioTuring License. The tool is now free for academic use.

For further enquiries, please contact us at

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