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Lasso specifications


Unique identifier OMICS_14285
Name Lasso
Alternative name Least absolute shrinkage and selection operator
Software type Package/Module
Interface Command line interface
Restrictions to use None
Operating system Unix/Linux, Mac OS, Windows
Programming languages R
Computer skills Advanced
Stability Stable
Maintained Yes




No version available



  • person_outline Yunli Wang

Publication for Least absolute shrinkage and selection operator

Lasso citations


Pancreatic ductal adenocarcinoma can be detected by analysis of volatile organic compounds (VOCs) in alveolar air

BMC Cancer
PMCID: 5935919
PMID: 29728093
DOI: 10.1186/s12885-018-4452-0

[…] Considering the large number of independent variables involved in the analysis, we decided to base the elaboration of the predictive model on a LASSO (Least Absolute Shrinkage and Selection Operator) logistic regression (LLR) [, ]. The LASSO is a penalized estimation method which avoids overfitting, caused by to collinearity or high-dimensionality o […]


A Temporal Examination of Platelet Counts as a Predictor of Prognosis in Lung, Prostate, and Colon Cancer Patients

Sci Rep
PMCID: 5920102
PMID: 29700384
DOI: 10.1038/s41598-018-25019-1

[…] All of the features were incorporated in a multivariate logistic regression model with LASSO (least absolute shrinkage and selection operator) regression analysis. The data was separated into training (2/3 of data) and test (1/3 of data) sets. After training and developing the model with the t […]


Global Correlates of Cardiovascular Risk: A Comparison of 158 Countries

PMCID: 5946196
PMID: 29587470
DOI: 10.3390/nu10040411
call_split See protocol

[…] range of problems associated with multicollinearity—the key statistical problem in the present study.Other tools that we used for the reduction of multicollinearity were the ridge regression, LASSO (least absolute shrinkage and selection operator) regression and elastic net regression. These regression methods are aimed at identifying the best predictors out of a set of variables that are mutuall […]


Association between Dietary Intake and Coronary Artery Calcification in Non Dialysis Chronic Kidney Disease: The PROGREDIR Study

PMCID: 5872790
PMID: 29562658
DOI: 10.3390/nu10030372
call_split See protocol

[…] Analyses were performed using SPSS software version 17.0 and R version 3.3.1 (generalized linear models and LASSO (least absolute shrinkage and selection operator) regression). Variables were tested for normality using the Kolmogorov–Smirnov test, and then differences between tertiles of CAC were tested using the […]


TIMSS 2011 Student and Teacher Predictors for Mathematics Achievement Explored and Identified via Elastic Net

Front Psychol
PMCID: 5862814
PMID: 29599736
DOI: 10.3389/fpsyg.2018.00317

[…] rowth of coefficients and thus are used to solve overfitting problems. Regularization can be carried out with penalized regression in statistics. Penalized regression techniques such as Ridge, LASSO (Least Absolute Shrinkage and Selection Operator), and elastic net have been widely applied to various fields of study including computer science/engineering (Keerthi and Shevade, ; Sun et al., ; Wang […]


Using single index ODEs to study dynamic gene regulatory network

PLoS One
PMCID: 5825071
PMID: 29474376
DOI: 10.1371/journal.pone.0192833

[…] ion procedure for model () based on the penalized profile least-squares approach as follows.Selecting variables by penalized least squares has been widely studied in literature. See, for example, the least absolute shrinkage and selection operator (LASSO) [], the smoothly clipped absolute deviation (SCAD) approach [], the adaptive lasso estimator [], the elastic-net estimator [] and the adaptive e […]


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Lasso institution(s)
National Research Council Canada, Ottawa, ON, Canada; National Research Council Canada, Fredericton, NB, Canada
Lasso funding source(s)
National Research Council Canada and Canadian Wheat Alliance supported this work.

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