What is the Xenium ‘Negative control probe counts per control per cell’ metric?

Question: What is the Xenium ‘Negative control probe counts per control per cell’ metric?

Answer: The 'Negative control probe counts per control per cell' metric assesses the rate of  high quality (>= Q20) negative control probe transcript counts, which when elevated can indicate suboptimal sample preparation.  

• This metric is present in Xenium v1.6+ software versions. The ‘High negative control probe counts per control per cell’ alert is based on this metric for v1.6+. For prior versions, a similar alert is based on the ‘Adjusted negative control probe rate’. The two metrics differ in their calculations.

• It is possible to re-process Xenium data from prior versions with the v1.6 standalone Xenium Ranger software to update results with the new metric.

Negative control probes are present in the probe pool but are not intended to bind nor ligate to transcript sequences. As such, their readout in the Xenium Onboard analysis represents background false positive signal. The metric is calculated as follows.

(Q20+ negative control probe counts)/(# control probes)/(# cells)

Xenium panels, including fully custom panels, generally have 20 negative control probes. The exception is the Xenium Mouse Brain Gene Expression panel, which has 27 negative control probes.

• Rates < 0.025 are considered low. If data also has low mean Q-Scores for gene transcripts, i.e. if the ‘Percent of all gene transcripts that are high quality’ alert is also present, then data is problematic. 
• Rates > 0.025 indicate elevated negative control probe rate. Elevated rates do not necessarily mean the quality of the data is poor. In most cases, the effect on downstream analyses will be minor. 

Contact support@10xgenomics.com to discuss optimizing sample preparation after considering the following.

1. Regardless of negative control probe counts, samples that present lower transcripts per cell are concerning. We consider 363 median transcripts per cell excellent.  
2. Are the UMAP clusters distinct? Does the cluster overlay on the tissue correspond to morphologically different regions, e.g. differential DAPI density regions? If so, the experiment captures cell type heterogeneity and tissue spatial structure.
3. Spatiality can help interpret the negative control rate further. Do the high quality (>= Q20) negative controls display spatiality, i.e. are more concentrated in non-tissue regions or are evenly dispersed across the tissue? If negative controls are concentrated in non-tissue areas or specific morphological regions, then factor for this when interpreting data quality. Some illustrative code towards plotting Xenium data is at https://kb.10xgenomics.com/hc/en-us/articles/11636252598925. 

Differences in the negative control probe rate across samples could reflect biological differences, sample quality differences or assay differences. For variable rates across samples, consider additionally factoring for cell density, e.g. does one sample have smaller cells or more cells per 100 µm² than the other samples? 

Related content

• The adjusted negative control probe rate appears elevated, what does this mean?

Product: Xenium In Situ Gene Expression
Last modified: August 11, 2023