Showing 9 of total 9 results (show query)
projectmosaic
mosaic:Project MOSAIC Statistics and Mathematics Teaching Utilities
Data sets and utilities from Project MOSAIC (<http://www.mosaic-web.org>) used to teach mathematics, statistics, computation and modeling. Funded by the NSF, Project MOSAIC is a community of educators working to tie together aspects of quantitative work that students in science, technology, engineering and mathematics will need in their professional lives, but which are usually taught in isolation, if at all.
Maintained by Randall Pruim. Last updated 1 years ago.
93 stars 13.32 score 7.2k scripts 7 dependents
kbroman
qtl:Tools for Analyzing QTL Experiments
Analysis of experimental crosses to identify genes (called quantitative trait loci, QTLs) contributing to variation in quantitative traits. Broman et al. (2003) <doi:10.1093/bioinformatics/btg112>.
Maintained by Karl W Broman. Last updated 7 months ago.
80 stars 12.79 score 2.4k scripts 29 dependents
bioc
CellNOptR:Training of boolean logic models of signalling networks using prior knowledge networks and perturbation data
This package does optimisation of boolean logic networks of signalling pathways based on a previous knowledge network and a set of data upon perturbation of the nodes in the network.
Maintained by Attila Gabor. Last updated 5 days ago.
cellbasedassayscellbiologyproteomicspathwaysnetworktimecourseimmunooncology
6.95 score 98 scripts 6 dependentsbioc
miQC:Flexible, probabilistic metrics for quality control of scRNA-seq data
Single-cell RNA-sequencing (scRNA-seq) has made it possible to profile gene expression in tissues at high resolution. An important preprocessing step prior to performing downstream analyses is to identify and remove cells with poor or degraded sample quality using quality control (QC) metrics. Two widely used QC metrics to identify a ‘low-quality’ cell are (i) if the cell includes a high proportion of reads that map to mitochondrial DNA encoded genes (mtDNA) and (ii) if a small number of genes are detected. miQC is data-driven QC metric that jointly models both the proportion of reads mapping to mtDNA and the number of detected genes with mixture models in a probabilistic framework to predict the low-quality cells in a given dataset.
Maintained by Ariel Hippen. Last updated 5 months ago.
singlecellqualitycontrolgeneexpressionpreprocessingsequencing
19 stars 6.39 score 65 scripts
inra
Rnmr1D:Perform the Complete Processing of a Set of Proton Nuclear Magnetic Resonance Spectra
Perform the complete processing of a set of proton nuclear magnetic resonance spectra from the free induction decay (raw data) and based on a processing sequence (macro-command file). An additional file specifies all the spectra to be considered by associating their sample code as well as the levels of experimental factors to which they belong. More detail can be found in Jacob et al. (2017) <doi:10.1007/s11306-017-1178-y>.
Maintained by Daniel Jacob. Last updated 3 days ago.
8 stars 5.98 score
lbbe-software
MareyMap:Estimation of Meiotic Recombination Rates Using Marey Maps
Local recombination rates are graphically estimated across a genome using Marey maps.
Maintained by Aurélie Siberchicot. Last updated 26 days ago.
1 stars 5.30 score 20 scriptsbioc
canceR:A Graphical User Interface for accessing and modeling the Cancer Genomics Data of MSKCC
The package is user friendly interface based on the cgdsr and other modeling packages to explore, compare, and analyse all available Cancer Data (Clinical data, Gene Mutation, Gene Methylation, Gene Expression, Protein Phosphorylation, Copy Number Alteration) hosted by the Computational Biology Center at Memorial-Sloan-Kettering Cancer Center (MSKCC).
Maintained by Karim Mezhoud. Last updated 5 months ago.
guigeneexpressionclusteringgogenesetenrichmentkeggmultiplecomparisoncancercancer-datagenegene-expressiongene-methylationgene-mutationgene-setsmethylationmskccmutationstcltk
7 stars 5.08 score 17 scriptsbioc
XAItest:XAItest: Enhancing Feature Discovery with eXplainable AI
XAItest is an R Package that identifies features using eXplainable AI (XAI) methods such as SHAP or LIME. This package allows users to compare these methods with traditional statistical tests like t-tests, empirical Bayes, and Fisher's test. Additionally, it includes a system that enables the comparison of feature importance with p-values by incorporating calibrated simulated data.
Maintained by Ghislain FIEVET. Last updated 7 days ago.
softwarestatisticalmethodfeatureextractionclassificationregression
2.95 score
kwb-r
kwb.epanet:R Package for Interfacing EPANET
Functions enabling the reading and writing of EPANET (http://www.epa.gov/nrmrl/wswrd/dw/epanet.html) input files and reading of output files.
Maintained by Hauke Sonnenberg. Last updated 3 years ago.
epanetmodellingpipe-networkproject-optiwells2
1.70 score 1 scripts