Analyzing RNA-Seq data from Chlamydia with super broad transcriptomic activation: challenges, solutions, and implications for other systems
This study highlights the limitations of standard RNA-Seq analysis tools in scenarios with extensive transcriptomic activation, such as in Chlamydia spp. during early infection. Our revised normalization methods, incorporating host reads or total sequencing depth, provide a more accurate representation of gene expression dynamics. These approaches may inform similar adjustments in other systems with unbalanced gene expression dynamics, enhancing the accuracy of transcriptomic analysis.
Authors
- Yuxuan Wang (ORCID: https://orcid.org/0000-0003-0771-1078)
- Danny Wan (ORCID: https://orcid.org/0000-0001-8262-8173)
- Guangming Zhong (ORCID: https://orcid.org/0000-0001-7053-5009)
- Huizhou Fan (ORCID: https://orcid.org/0000-0002-4903-926X)
- Andrew Y. S. Cheng (ORCID: https://orcid.org/0000-0002-9155-6156)
- Wei Vivian Li (ORCID: https://orcid.org/0000-0002-2087-2709)
Institutions
- Rutgers, The State University of New Jersey (US)
- University of California, Riverside (US)
- The University of Texas at San Antonio Health Science Center (US)
- Johnson University (US)
- The University of Texas at San Antonio (US)
Publication Details
- Journal
- BMC Genomics
- Published
- 2024-08-25
- DOI
- https://doi.org/10.1186/s12864-024-10714-3
- Citations
- 3
- Primary Topic
- Reproductive tract infections research
- Type
- article
- Field-Weighted Citation Impact
- 1.03
Funders
- National Institutes of Health