Figures & data
Figure 1. Identification of FMT recipient factors that predict HOMA-IR responses by machine learning.
![Figure 1. Identification of FMT recipient factors that predict HOMA-IR responses by machine learning.](/cms/asset/89d72716-73d0-4ad0-9343-d6ee3aa50f8f/kgmi_a_2345134_f0001_oc.jpg)
Figure 2. FMT recipient factors at baseline are associated with the differences in fecal microbiota changes in diversity between responders and non-responders in HOMA-IR.
![Figure 2. FMT recipient factors at baseline are associated with the differences in fecal microbiota changes in diversity between responders and non-responders in HOMA-IR.](/cms/asset/2dc4ea1a-fee5-4d0b-bf54-dc123fff2676/kgmi_a_2345134_f0002_oc.jpg)
Figure 3. FMT recipient baseline factors predict donor-specific ASVs engraftment.
![Figure 3. FMT recipient baseline factors predict donor-specific ASVs engraftment.](/cms/asset/d69ec2a1-10ed-470e-b25f-154761c04d95/kgmi_a_2345134_f0003_oc.jpg)
Supplemental Material
Download Zip (1.8 MB)Data availability statement
The raw sequencing data have been deposited into the Sequence Read Archive (SRA) of the NCBI (http://www.ncbi.nlm.nih.gov/sra) under BioProject PRJNA708262. All other relevant data related to the current study are freely available from the corresponding author (K.L.M.) upon request, which does not include confidential patient information.