Leuk_miR_filt: microRNA expression of acute leukemia phenotypes (filtered...

In juliancandia/eNetXplorer: Quantitative Exploration of Elastic Net Families for Generalized Linear Models

microRNA expression of acute leukemia phenotypes (filtered dataset)

Description

Data of human microRNA (miR) expression of 370 miRs from 80 acute myeloid (AML) and acute lymphoblastic (ALL) leukemia cell lines and 60 primary (patient) samples. Acute lymphoblastic leukemia samples are further classified by B-cell (B-ALL) and T-cell (T-ALL) subphenotypes.

Format

The filtered dataset Leuk_miR_filt consists of a numerical matrix of predictors (with samples as rows and miRs as columns) and two categorical response vectors provided for binomial (AML, ALL) and multinomial (AML, B-ALL, T-ALL) classification.

Details

The filtered dataset Leuk_miR_filt is a subset of the full dataset Leuk_miR_full, which includes only miRs with median expression >1.2 across all samples. Only leukemia samples (cell lines and primary) were kept. Data available at GEO under Accession Number GSE51908.

References

Tan YS et al. Regulation of RAB5C is important for the growth inhibitory effects of MiR-509 in human precursor-B acute lymphoblastic leukemia, PLoS One (2014) 9:e111777.

Candia J et al. Uncovering low-dimensional, miR-based signatures of acute myeloid and lymphoblastic leukemias with a machine-learning-driven network approach, Converg Sci Phys Oncol (2015) 1:025002.

Examples

# Multinomial models to predict acute myeloid (AML), acute B-cell lymphoblastic 
# (B-ALL) and acute T-cell lymphoblastic (T-ALL) leukemias:
data(Leukemia_miR)
fit = eNetXplorer(x=Leuk_miR_filt$predictor, y=Leuk_miR_filt$response_multinomial,
family="multinomial", n_run=25, n_perm_null=15, seed=111)

juliancandia/eNetXplorer documentation built on May 11, 2023, 1:59 a.m.