AllData_V2.0: All the training data FIT is based on
In RachellyN/FIT: Predicts human disease relevant genes from mouse model gene expression, based on prior mouse and human gene expression comparisons
Description
Comprised of gene level expression data of 170 cross-species pairs (CSP).
Usage
1
Format
A data frame with 1,737,091 rows and 11 columns:
- Disease
The disease of the dataset
- DataType
Details the technology(RNAseq/ microarrays) and the type of the CSP (standard dataset (ST) or reference (RF)), in the format <technology>_<type>
- CSP_ID
A unique identifier for the CSP
- MM.Entrez
Mouse Entrez ID
- HS.Entrez
Human Entrez ID
- FC.HS
Human fold-change
- FC.MM
Mouse fold-change
- EffSize.HS
Human effect size
- EffSize.MM
Mouse effect size
- qval.HS
Human q-value
- qval.MM
Mouse q-value
RachellyN/FIT documentation built on May 16, 2019, 6:59 p.m.
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Description
Comprised of gene level expression data of 170 cross-species pairs (CSP).
Usage
1 |
Format
A data frame with 1,737,091 rows and 11 columns:
- Disease
The disease of the dataset
- DataType
Details the technology(RNAseq/ microarrays) and the type of the CSP (standard dataset (ST) or reference (RF)), in the format <technology>_<type>
- CSP_ID
A unique identifier for the CSP
- MM.Entrez
Mouse Entrez ID
- HS.Entrez
Human Entrez ID
- FC.HS
Human fold-change
- FC.MM
Mouse fold-change
- EffSize.HS
Human effect size
- EffSize.MM
Mouse effect size
- qval.HS
Human q-value
- qval.MM
Mouse q-value
R Package Documentation
Browse R Packages
We want your feedback!
Note that we can't provide technical support on individual packages. You should contact the package authors for that.
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