Human Salivary Microbiome Data for BMI Inference in Forensic Research

Microbial community composition data from human saliva samples, sequenced via 16S rRNA, to investigate associations with body mass index (BMI). The dataset was created by Jingyan Ji and last updated on 2026-04-21. It is a pilot study with a file size of 943.2 KB, indicating a limited scope.

Use Cases

• Training random forest models for BMI category inference based on microbial marker abundance.
• Identifying BMI-associated microbial taxa, such as Neisseria and Veillonella, using linear discriminant analysis.
• Conducting principal coordinates analysis to separate microbial communities from different BMI groups.
• Screening for forensic-relevant microbial indicators in saliva using statistical tests like Kruskal–Wallis.

Strengths

• Identifies 22 specific microbial taxa with significantly different abundance across BMI groups.
• Includes results from a constructed random forest model that accurately inferred BMI categories for most samples.
• Data is openly shared under a CC-BY-4.0 license.

Limitations

• Row count is unknown, which may limit suitability assessment.
• Column-level documentation is absent; field semantics must be inferred after download.
• Description metadata is limited; actual data quality requires manual inspection after download.

Provenance

Source

figshare, author Jingyan Ji.

Collection Method

Saliva samples were collected and subjected to 16S rRNA sequencing.

Freshness

Last updated 2026-04-21 05:24:33; freshness should be verified.