Pinned Repositories
MicrobiomeStat
Track, Analyze, Visualize: Unravel Your Microbiome's Temporal Pattern with MicrobiomeStat
AcNutrients
coral_disease_resistance_microbiome
Analysis for the microbiomes of corals that were tested for disease resilience and susceptibility in nursery-reared Caribbean Acropora spp. Diseased coral were grafted onto healthy fragments and diseased fragments may have harbored distinct pathogens.
CoralPersistence
Larvae_Sediment
q2-SCNIC
A QIIME2 plugin for running SCNIC
RESISTADA_Microbiome
SCTLD-zones
SCTLD_16S_2019
Microbiome analysis to compare corals affected by Stony Coral Tissue Loss Disease (SCTLD) and apparently healthy corals, and the microbiome analysis of sediment and seawater samples collected before, during, and after SCTLD's arrival at a reef.
SCTLD_microbiome_meta_analysis
The goal of this study is to conduct a meta-analysis of publicly available and unpublished SCLTD microbiome datasets. In doing this we aim to: (1) Characterize the microbiome of SCTLD across region, species, year, and studies. (2) Identify drivers leading to variation among datasets.
srosales712's Repositories
srosales712/RESISTADA_Microbiome
srosales712/AcNutrients
srosales712/coral_disease_resistance_microbiome
Analysis for the microbiomes of corals that were tested for disease resilience and susceptibility in nursery-reared Caribbean Acropora spp. Diseased coral were grafted onto healthy fragments and diseased fragments may have harbored distinct pathogens.
srosales712/CoralPersistence
srosales712/Larvae_Sediment
srosales712/q2-SCNIC
A QIIME2 plugin for running SCNIC
srosales712/SCTLD-zones
srosales712/SCTLD_16S_2019
Microbiome analysis to compare corals affected by Stony Coral Tissue Loss Disease (SCTLD) and apparently healthy corals, and the microbiome analysis of sediment and seawater samples collected before, during, and after SCTLD's arrival at a reef.
srosales712/SCTLD_microbiome_meta_analysis
The goal of this study is to conduct a meta-analysis of publicly available and unpublished SCLTD microbiome datasets. In doing this we aim to: (1) Characterize the microbiome of SCTLD across region, species, year, and studies. (2) Identify drivers leading to variation among datasets.