it enables a streamlined data reanalysis because each row/line of the SDRF can be processed individually. In addition, it facilitates meta-analysis with simple operations such as merging different SDRFs coming from different datasets or splitting an SDRF for a given dataset by a specific property...
ENViz: a Cytoscape App for integrated statistical analysis and visualization of sample-matched data with multiple data types.doi:10.1093/bioinformatics/btu853ENViz (Enrichment Analysis and Visualization) is a Cytoscape app that performs joint enrichment analysis of two types of sample matched datasets ...
2.4 Datasets used in tests All the datasets presented in the previous section were used in the tests we conducted. However, they differ significantly in size. For example, the OSD dataset, with no more than one hundred samples is eclipsed by the TOD dataset, where tens of thousands of sampl...
Flow cytometry technique produces large, multi-dimensional datasets of individual cells that are helpful for biomedical science and clinical research. Given the size of the data, efficient computational analysis techniques are necessary to assist researchers in understanding and inter-preting the data. Au...
Future research should consider employing datasets with finer population segmentation to allow for more precise conclusions through stratified analysis. Lastly, it is important to note that our study population consisted exclusively of individuals of European ancestry, potentially limiting the generalizability ...
Usesdarufor storing data and basic statistics. Statsample::Multiset: multiple datasets with same fields and type of vectors Anova module provides generic Statsample::Anova::OneWay and vector based Statsample::Anova::OneWayWithVectors. Also you can create contrast using Statsample::Anova::Contrast...
the performance of five ML methods using simulated datasets and three real datasets to derive the criteria for sample size. We systematically increase the sample size, starting from 16, by randomly sampling and examine the impact of sample size on classifiers’ performance and both effect sizes. ...
High-quality datasets are essential to support hydrological science and modeling. Several CAMELS (Catchment Attributes and Meteorology for Large-sample Studies) datasets exist for specific countries or regions, however these datasets lack standardization
In essence, scMerge2 takes gene expression matrices from a collection of datasets and integrates them in a hierarchical manner. The final output of scMerge2 is a single adjusted expression matrix with all input data matrices merged and ready for downstream analysis. Fig. 1: Overview of scMerge...
as well as multiple tissues and multiple chemical compounds, which was the source of Isomap's success. Another prerequisite for a successful application of Isomap is a large enough number of samples. Isomap will become really useful when datasets with hundreds or thousands of microarrays need to ...