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http://cran.r-project.org/web/packages/MetaQC/

Software for quality control and diagnosis for microarray meta-analysis. Quantitative quality control measures include: (1) internal homogeneity of co-expression structure among studies (internal quality control; IQC); (2) external consistency of co-expression structure correlating with pathway database (external quality control; EQC); (3) accuracy of differentially expressed gene detection (accuracy quality control; AQCg) or pathway identification (AQCp); (4) consistency of differential expression ranking in genes (consistency quality control; CQCg) or pathways (CQCp). For each quality control index, the p-values from statistical hypothesis testing are minus log transformed and PCA biplots were applied to assist visualization and decision. Results generate systematic suggestions to exclude problematic studies in microarray meta-analysis and potentially can be extended to GWAS or other types of genomic meta-analysis. The identified problematic studies can be scrutinized to identify technical and biological causes (e.g. sample size, platform, tissue collection, preprocessing etc) of their bad quality or irreproducibility for final inclusion / exclusion decision.

Proper citation: MetaQC (RRID:SCR_006000) Copy   

•   Source: SciCrunch Registry

http://cran.r-project.org/web/packages/QCGWAS/

Software tools for (automated and manual) quality control of the results of Genome Wide Association Studies.

Proper citation: QCGWAS (RRID:SCR_006408) Copy   

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https://github.com/ggloor/ALDEx2

Software tool to examine compositional high-throughput sequence data with Welch's t-test. A differential relative count abundance analysis for the comparison of two conditions. For example, single-organism and meta-rna-seq high-throughput sequencing assays, or of selected and unselected values from in-vitro sequence selections. Uses a Dirichlet-multinomial model to infer abundance from counts, that has been optimized for three or more experimental replicates. Infers sampling variation and calculates the expected Benjamini-Hochberg false discovery rate given the biological and sampling variation using several parametric and non-parametric tests. Can to glm and Kruskal-Wallace tests on one-way ANOVA style designs.

Proper citation: ALDEx2 (RRID:SCR_003364) Copy   

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http://cran.r-project.org/web/packages/RCircos/

Software package that provides a simple and flexible way to generate Circos 2D track plot images for genomic data visualization. The types of plots include: heatmap, histogram, lines, scatterplot, tiles and plot items for further decorations include connector, link (lines and ribbons), and text (gene) label. All functions require only R graphics package that comes with R base installation.

Proper citation: RCircos (RRID:SCR_003310) Copy   

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

An R package for extending the grammar of graphics for genomic data. The graphics are designed to answer common scientific questions, in particular those often asked of high throughput genomics data. All core Bioconductor data structures are supported, where appropriate. The package supports detailed views of particular genomic regions, as well as genome-wide overviews. Supported overviews include ideograms and grand linear views. High-level plots include sequence fragment length, edge-linked interval to data view, mismatch pileup, and several splicing summaries.

Proper citation: ggbio (RRID:SCR_003313) Copy   

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

An R software application and package used to generate high-quality circular plots for visualizing genomic variations, including mutation patterns, copy number variations (CNVs), expression patterns, and methylation patterns.

Proper citation: OmicCircos (RRID:SCR_003292) Copy   

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http://cran.r-project.org/web/packages/MultiPhen/

Software package that performs genetic association tests between SNPs (one-at-a-time) and multiple phenotypes (separately or in joint model).

Proper citation: MultiPhen (RRID:SCR_003498) Copy   

•   Source: SciCrunch Registry

https://github.com/alyssafrazee/polyester

An R package designed to simulate RNA sequencing experiments with differential transcript expression. Given a set of annotated transcripts, it will simulate the steps of an RNA-seq experiment (fragmentation, reverse-complementing, and sequencing) and produce files containing simulated RNA-seq reads. Simulated reads can be analyzed using a choice of downstream analysis tools. Polyester has a built-in wrapper function to simulate a case/control experiment with differential transcript expression and biological replicates. Users are able to set the levels of differential expression at transcripts of their choosing. This means they know which transcripts are differentially expressed in the simulated dataset, so accuracy of statistical methods for differential expression detection can be analyzed. Polyester offers several unique features: * Built-in functionality to simulate differential expression at the transcript level * Ability to explicitly set differential expression signal strength * Simulation of small datasets, since large RNA-seq datasets can require lots of time and computing resources to analyze * Generation of raw RNA-seq reads, as opposed to alignments or transcript-level abundance estimates * Transparency/open-source code

Proper citation: Polyester (RRID:SCR_003602) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/edgeR/

Bioconductor software package for Empirical analysis of Digital Gene Expression data in R. Used for differential expression analysis of RNA-seq and digital gene expression data with biological replication.

Proper citation: edgeR (RRID:SCR_012802) Copy   

•   Source: SciCrunch Registry

http://www.dkfz.de/en/epidemiologie-krebserkrankungen/software/software.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May 24,2023. Software program that performs estimation of power and sample sizes required to detect genetic and environmental main, as well as gene-environment interaction (GxE) effects in indirect matched case-control studies (1:1 matching). When the hypothesis of GxE is tested, power/sample size will be estimated for the detection of GxE, as well as for the detection of genetic and environmental marginal effects. Furthermore, power estimation is implemented for the joint test of genetic marginal and GxE effects (Kraft P et al., 2007). Power and sample size estimations are based on Gauderman''s (2002) asymptotic approach for power and sample size estimations in direct studies of GxE. Hardy-Weinberg equilibrium and independence of genotypes and environmental exposures in the population are assumed. The estimates are based on genotypic codes (G=1 (G=0) for individuals who carry a (non-) risk genotype), which depend on the mode of inheritance (dominant, recessive, or multiplicative). A conditional logistic regression approach is used, which employs a likelihood-ratio test with respect to a biallelic candidate SNP, a binary environmental factor (E=1 (E=0) in (un)exposed individuals), and the interaction between these components. (entry from Genetic Analysis Software)

Proper citation: PIAGE (RRID:SCR_013124) Copy   

•   Source: SciCrunch Registry

http://folk.uio.no/thoree/FEST/

An R package for simulations and likelihood calculations of pair-wise family relationships using DNA marker data. (entry from Genetic Analysis Software)

Proper citation: R/FEST (RRID:SCR_013347) Copy   

•   Source: SciCrunch Registry

http://www.arrayanalysis.org/

Tools for microarray quality control and pre-processing.

Proper citation: ArrayAnalysis.org (RRID:SCR_010932) Copy   

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https://bioconductor.org/packages/release/bioc/html/oligo.html

Software package to analyze oligonucleotide arrays (expression/SNP/tiling/exon) at probe-level. It currently supports Affymetrix (CEL files) and NimbleGen arrays (XYS files).

Proper citation: oligo (RRID:SCR_015729) Copy   

•   Source: SciCrunch Registry

http://CRAN.R-project.org/package=LMERConvenienceFunctions

Software package that performs backward selection of fixed effects, forward fitting of the random effects, and post-hoc analysis using parallel capabilities. Other functionality includes the computation of ANOVAs with upper- or lower-bound p-values and R-squared values for each model term, model criticism plots, data trimming on model residuals, and data visualization.

Proper citation: R package: LMERConvenienceFunctions (RRID:SCR_015658) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/web/packages/lattice/index.html

Data visualization software inspired by Trellis graphics, with an emphasis on multivariate data. Lattice is sufficient for typical graphics needs as well as most nonstandard requirements.

Proper citation: R package: lattice (RRID:SCR_015662) Copy   

•   Source: SciCrunch Registry

https://github.com/hpardoe/napr/

Cloud-based framework that allows users to estimate the age of individual subjects using cortical thickness maps derived from their own locally processed T1-weighted whole brain MRI scans. The provided age prediction models were trained using (i) relevance vector machines and (ii) Gaussian processes machine learning methods applied to cortical thickness surfaces obtained using Freesurfer v5.3.

Proper citation: NAPR: Neuroanatomical Age Prediction using R (RRID:SCR_015759) Copy   

•   Source: SciCrunch Registry

http://www.statsmodels.org/

Statistical software that provides classes and functions for the estimation of many different models, as well as for conducting statistical tests, and statistical data exploration. The results are tested against existing statistical packages to ensure that they are correct. http://conference.scipy.org/proceedings/scipy2010/seabold.html

Proper citation: statsmodel (RRID:SCR_016074) Copy   

•   Source: SciCrunch Registry

http://pages.stat.wisc.edu/~yandell/qtl/software/qtlbim/

Software library for QTL Bayesian Interval Mapping that provides a Bayesian model selection approach to map multiple interacting QTL. It works on experimentally inbred lines and performs a genome-wide search to locate multiple potential QTL. The package can handle continuous, binary and ordinal traits. (entry from Genetic Analysis Software)

Proper citation: R/QTLBIM (RRID:SCR_009375) Copy   

•   Source: SciCrunch Registry

https://cran.r-project.org/web/packages/HMP/index.html

An R-package which uses Dirichlet-Multinomial distribution to perform formal hypothesis testing on the species abundance distribution of human microbiome data, and to calculate power and sample size requirements for human microbiome experiments.

Proper citation: Hypothesis Testing and Power Calculations for Comparing Metagenomic Samples from HMP (RRID:SCR_014612) Copy   

•   Source: SciCrunch Registry

http://stat.ethz.ch/R-manual/R-patched/library/stats/html/hclust.html

R documentation for hierarchical cluster analysis on a set of dissimilarities for n objects. Each object is assigned to its own cluster, which an algorithm proceeds through iteratively. Two of the most similar clusters are joined at each stage until there is a single cluster. Distances between clusters are recomputed at each stage by the Lance–Williams dissimilarity update formula according to the particular clustering method being used. Clustering methods include: Ward's minimum variance method, complete linkage method, and single linkage method.

Proper citation: Hierarchical Clustering (RRID:SCR_014673) Copy   

•   Source: SciCrunch Registry