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http://www.bioconductor.org/packages/2.0/bioc/html/SNPchip.html

Software package that contains classes and methods useful for storing, visualizing and analyzing high density SNP data. Originally developed from the SNPscan web-tool, SNPchip utilizes S4 classes and extends other open source R tools available at Bioconductor, including the R packages Biobase and oligo. This has numerous advantages, including the ability to build statistical models for SNP-level data that operate on instances of the class, and to communicate with other R packages that add additional functionality.

Proper citation: SNPchip (RRID:SCR_001269) Copy   

•   Source: SciCrunch Registry

https://dalexander.github.io/admixture/download.html

A software tool for maximum likelihood estimation of individual ancestries from multilocus SNP genotype datasets. It uses the same statistical model as STRUCTURE but calculates estimates much more rapidly using a fast numerical optimization algorithm. It uses a block relaxation approach to alternately update allele frequency and ancestry fraction parameters. Each block update is handled by solving a large number of independent convex optimization problems, which are tackled using a fast sequential quadratic programming algorithm. Convergence of the algorithm is accelerated using a novel quasi-Newton acceleration method., THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 16,2025.

Proper citation: ADMIXTURE (RRID:SCR_001263) Copy   

•   Source: SciCrunch Registry

http://med.stanford.edu/tanglab/software/frappe.html

Software using a f frequentist approach for estimating individual ancestry proportion.

Proper citation: frappe (RRID:SCR_001264) Copy   

•   Source: SciCrunch Registry

https://cran.r-universe.dev/IPCAPS

Software implementing a population structure analysis algorithm which assigns individuals to subpopulations and infers the total number of subpopulations present. Additional functions have been included that result in improved population assignment accuracy. # Universal genotype data encoding scheme which allows the population analysis of all types of genetic markers; Single Nucleotide Polymorphism (SNP), Short Tandem Repeat (STR) and RFLP. # New termination criterion called ?EigenDev? which is more robust to population sampling, thus provides the better estimation of number of assigned subpopulations (K) and higher accuracy for the analysis of large complex population datasets.

Proper citation: ipPCA (RRID:SCR_001262) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/devel/bioc/html/VegaMC.html

Software package that enables the detection of driver chromosomal imbalances including loss of heterozygosity (LOH) from array comparative genomic hybridization (aCGH) data. It performs a joint segmentation of a dataset and uses a statistical framework to distinguish between driver and passenger mutation. VegaMC has been implemented so that it can be immediately integrated with the output produced by PennCNV tool. In addition, it produces in output two web pages that allows a rapid navigation between both the detected regions and the altered genes. In the web page that summarizes the altered genes, the link to the respective Ensembl gene web page is reported.

Proper citation: VegaMC (RRID:SCR_001267) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.1/bioc/html/VanillaICE.html

Software package using Hidden Markov Models for characterizing chromosomal alterations in high throughput SNP arrays.

Proper citation: VanillaICE (RRID:SCR_001268) Copy   

•   Source: SciCrunch Registry

http://www.wpic.pitt.edu/wpiccompgen/GemTools/GemTools.htm

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Software tools for modeling genetic ancestry based on the single nucleotide polymorphism (SNP) information. This package of functions helps the user account for genetic ancestry of a large number of individuals using spectral graph theory and projections to break a large problem into smaller pieces and calculate genetic ancestry information efficiently, i.e., a divide and conquer (dac) strategy. It is completely written in R and runs on any platform that supports R.

Proper citation: GemTools (RRID:SCR_001259) Copy   

•   Source: SciCrunch Registry

https://rdrr.io/bioc/sRAP/

Software package that provides a pipeline for gene expression analysis (primarily for RNA-Seq data). The normalization function is specific for RNA-Seq analysis, but all other functions (Quality Control Figures, Differential Expression and Visualization, and Functional Enrichment via BD-Func) will work with any type of gene expression data.

Proper citation: sRAP (RRID:SCR_001297) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/SCAN.UPC.html

A microarray normalization software (SCAN) to facilitate personalized-medicine workflows with an extension (UPC) that estimates whether a given gene/transcript is active above background levels in a given sample. Rather than processing microarray samples as groups, which can introduce biases and present logistical challenges, SCAN normalizes each sample individually by modeling and removing probe- and array-specific background noise using only data from within each array. SCAN can be applied to one-channel (e.g., Affymetrix) or two-channel (e.g., Agilent) microarrays. The UPC method can be applied to one-channel or two-channel microarrays as well as to RNA-Seq read counts. Because UPC values are represented on the same scale and have an identical interpretation for each platform, they can be used for cross-platform data integration. A

Proper citation: SCAN.UPC (RRID:SCR_001334) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/snm.html

Software package that uses a modeling strategy especially designed for normalizing high-throughput genomic data. The premise is that your data is a function of study-specific variables which are either biological variables that represent the target of the statistical analysis, or adjustment variables that represent factors arising from the experimental or biological setting the data is drawn from. The SNM approach aims to simultaneously model all study-specific variables in order to more accurately characterize the biological or clinical variables of interest.

Proper citation: SNM (RRID:SCR_001299) Copy   

•   Source: SciCrunch Registry

https://rdrr.io/bioc/betr/man/betr.html#heading-0

Software package that implements the Bayesian Estimation of Temporal Regulation algorithm to identify differentially expressed genes in microarray time-course data.

Proper citation: betr (RRID:SCR_001332) Copy   

•   Source: SciCrunch Registry

http://www.roche.com/

A Swiss global health-care company that operates under two divisions: Pharmaceuticals and Diagnostics.

Proper citation: Roche (RRID:SCR_001326) Copy   

•   Source: SciCrunch Registry

https://bioconductor.org/packages//2.11/bioc/html/gprege.html

Software R package for Gaussian Process Ranking and Estimation of Gene Expression time-series. The software fits two Gaussian processes (GPs) with an radial basis function (RBF) (+ noise diagonal) kernel on each profile. One GP kernel is initialized wih a short lengthscale hyperparameter, signal variance as the observed variance and a zero noise variance. It is optimized via scaled conjugate gradients (netlab). A second GP has fixed hyperparameters: zero inverse-width, zero signal variance and noise variance as the observed variance. The log-ratio of marginal likelihoods of the two hypotheses acts as a score of differential expression for the profile. Comparison via receiver operating characteristic curves (ROC curves) is performed against Bayesian hierarchical model for the analysis of time-series (BATS) (Angelini et.al, 2007).

Proper citation: gprege (RRID:SCR_001324) Copy   

•   Source: SciCrunch Registry

http://sourceforge.net/projects/kanalyze/

A Java toolkit designed to convert DNA and RNA sequences into k-mers.

Proper citation: KAnalyze (RRID:SCR_001323) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/AffyExpress.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Software package for quality assessment and to identify differentially expressed genes in the Affymetrix gene expression data.

Proper citation: AffyExpress (RRID:SCR_001321) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/beadarray.html

Software package to read bead-level data (raw TIFFs and text files) output by BeadScan as well as bead-summary data from BeadStudio. Methods for quality assessment and low-level analysis are provided.

Proper citation: beadarray (RRID:SCR_001314) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/arrayMvout.html

Software package that supports the application of diverse quality metrics to AffyBatch instances, summarizing these metrics via PCA, and then performing parametric outlier detection on the PCs to identify aberrant arrays with a fixed Type I error rate.

Proper citation: arrayMvout (RRID:SCR_001317) Copy   

•   Source: SciCrunch Registry

https://www.bioconductor.org/packages//2.7/bioc/html/affyQCReport.html

Software package to create a QC report for an AffyBatch object. The report is intended to allow the user to quickly assess the quality of a set of arrays in an AffyBatch object.

Proper citation: affyQCReport (RRID:SCR_001318) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/maCorrPlot.html

Software that graphically displays correlation in microarray data that is due to insufficient normalization.

Proper citation: maCorrPlot (RRID:SCR_001348) Copy   

•   Source: SciCrunch Registry

http://www.bioinf.jku.at/software/farms/farms.html

Software using a model-based technique for summarizing high-density oligonucleotide array data at probe level for Affymetrix GeneChips. It is based on a factor analysis model for which a Bayesian maximum a posteriori method optimizes the model parameters under the assumption of Gaussian measurement noise.

Proper citation: FARMS (RRID:SCR_001344) Copy   

•   Source: SciCrunch Registry