Hi,
I am planning on doing a single cell atac sequencing of tumor infiltrating CD8 T cells of WT and KO mice.
Due to cost issues i would only be able to afford to send two samples (n=1 each, essentially)
Would i still be able to have statistically significant or publishable data out of this?
Many thanks
Hello,
This is a very relevant question, as experimental design and sample size are critical in single-cell sequencing studies. In your case, working with only two samples (n = 1 per group), there are several aspects to consider:
1. Biological variability: With n = 1 per group, it is difficult to determine whether observed differences are due to the experimental condition (WT vs. KO) or natural variability between individuals. In single-cell studies, cellular heterogeneity can be high, even within the same sample, which complicates the interpretation of results.
2. Statistical significance: With only one individual per group, it is not possible to perform robust statistical analyses to compare conditions. The results might be interesting from an exploratory perspective, but they would not be statistically significant or conclusive.
3. Exploratory value: Although not ideal, a study with n = 1 can serve as a pilot to identify trends or hypotheses that can later be validated with a larger sample size. However, it is important to be transparent about the limitations of the study when communicating results.
4. Publishability: Depending on the journal and field, studies with n = 1 may not be considered sufficient for publication, unless it is an exceptional case or the findings are highly novel and supported by additional validations (e.g., functional experiments or data from independent cohorts).
Recommendations:
- If possible, try pooling cells from multiple individuals into a single sample to increase cellular diversity and reduce reliance on a single individual.
- Consider complementing the study with more cost-effective techniques (e.g., qPCR or flow cytometry) to validate key findings.
- If the budget is limited, you could prioritize a more targeted approach (e.g., analyzing only specific genomic regions) rather than full sequencing.
In summary, while the data might be interesting, it is unlikely to be statistically significant or publishable with n = 1 per group. I would recommend exploring options to increase the sample size or adjust the experimental design to maximize the impact of the results.
Good luck with your project!