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Mendeley readers
Attention Score in Context
| Title |
MiRKAT-S: a community-level test of association between the microbiota and survival times
|
|---|---|
| Published in |
Microbiome, February 2017
|
| DOI | 10.1186/s40168-017-0239-9 |
| Pubmed ID | |
| Authors |
Anna Plantinga, Xiang Zhan, Ni Zhao, Jun Chen, Robert R. Jenq, Michael C. Wu |
| Abstract |
Community-level analysis of the human microbiota has culminated in the discovery of relationships between overall shifts in the microbiota and a wide range of diseases and conditions. However, existing work has primarily focused on analysis of relatively simple dichotomous or quantitative outcomes, for example, disease status or biomarker levels. Recently, there is also considerable interest in the relationship between the microbiota and censored survival outcomes, such as in clinical trials. How to conduct community-level analysis with censored survival outcomes is unclear, since standard dissimilarity-based tests cannot accommodate censored survival times and no alternative methods exist. We develop a new approach, MiRKAT-S, for community-level analysis of microbiome data with censored survival times. MiRKAT-S uses ecologically informative distance metrics, such as the UniFrac distances, to generate matrices of pairwise distances between individuals' taxonomic profiles. The distance matrices are transformed into kernel (similarity) matrices, which are used to compare similarity in the microbiota to similarity in survival times between individuals. Simulation studies using synthetic microbial communities demonstrate correct control of type I error and adequate power. We also apply MiRKAT-S to examine the relationship between the gut microbiota and survival after allogeneic blood or bone marrow transplant. We present MiRKAT-S, a method that facilitates community-level analysis of the association between the microbiota and survival outcomes and therefore provides a new approach to analysis of microbiome data arising from clinical trials. |
X Demographics
The data shown below were collected from the profiles of 5 X users who shared this research output. Click here to find out more about how the information was compiled.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| France | 1 | 20% |
| Unknown | 4 | 80% |
Demographic breakdown
| Type | Count | As % |
|---|---|---|
| Members of the public | 5 | 100% |
Mendeley readers
The data shown below were compiled from readership statistics for 60 Mendeley readers of this research output. Click here to see the associated Mendeley record.
Geographical breakdown
| Country | Count | As % |
|---|---|---|
| United States | 1 | 2% |
| Unknown | 59 | 98% |
Demographic breakdown
| Readers by professional status | Count | As % |
|---|---|---|
| Researcher | 19 | 32% |
| Student > Ph. D. Student | 10 | 17% |
| Student > Master | 6 | 10% |
| Student > Doctoral Student | 3 | 5% |
| Professor | 3 | 5% |
| Other | 6 | 10% |
| Unknown | 13 | 22% |
| Readers by discipline | Count | As % |
|---|---|---|
| Agricultural and Biological Sciences | 9 | 15% |
| Mathematics | 8 | 13% |
| Biochemistry, Genetics and Molecular Biology | 5 | 8% |
| Immunology and Microbiology | 5 | 8% |
| Medicine and Dentistry | 4 | 7% |
| Other | 12 | 20% |
| Unknown | 17 | 28% |
Attention Score in Context
This research output has an Altmetric Attention Score of 4. This is our high-level measure of the quality and quantity of online attention that it has received. This Attention Score, as well as the ranking and number of research outputs shown below, was calculated when the research output was last mentioned on 16 February 2017.
All research outputs
#7,203,969
of 22,952,268 outputs
Outputs from Microbiome
#1,294
of 1,449 outputs
Outputs of similar age
#137,695
of 420,410 outputs
Outputs of similar age from Microbiome
#41
of 44 outputs
Altmetric has tracked 22,952,268 research outputs across all sources so far. This one has received more attention than most of these and is in the 68th percentile.
So far Altmetric has tracked 1,449 research outputs from this source. They typically receive a lot more attention than average, with a mean Attention Score of 40.3. This one is in the 10th percentile – i.e., 10% of its peers scored the same or lower than it.
Older research outputs will score higher simply because they've had more time to accumulate mentions. To account for age we can compare this Altmetric Attention Score to the 420,410 tracked outputs that were published within six weeks on either side of this one in any source. This one has gotten more attention than average, scoring higher than 66% of its contemporaries.
We're also able to compare this research output to 44 others from the same source and published within six weeks on either side of this one. This one is in the 6th percentile – i.e., 6% of its contemporaries scored the same or lower than it.