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http://bioinf.spbau.ru/quast

Quality assessment software tool for evaluating and comparing genome assemblies. It works both with and without a given reference genome. It produces many reports, summary tables and plots.

Proper citation: QUAST (RRID:SCR_001228) Copy   

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http://denverlab.science.oregonstate.edu/tileqc/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on May,10, 2021.Software providing a visually oriented tile based approach to error detection for Solexa next-gen sequencing data. It is written in R and has both qualitative and quantitative error detection features. This software was written with the idea that the researcher's visual pattern recognition is the best way to detect novel errors and contains variety of ways to visualize that data. Once a new type of error is identified the data extraction features of the program may then be used as a starting point for the programmatic detection and/or filtration of similar errors. A supplementary role of tileQC is to convert the Eland and Q-score data contained within the Solexa "*_prb.txt" and "*_eland_results.txt" text files to a more flexible database form. Once in database form, tileQC simplifies the mechanics of interacting with that data and supplements standard SQL with an expression subsitution mechanism that allows R to be easily comingled with SQL. This system requires access to a mySQL server and the R package RMySQL as well as a few standard UNIX tools (also available on Windows and Macintosh).

Proper citation: TileQC (RRID:SCR_001229) Copy   

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http://www.broadinstitute.org/science/programs/genome-biology/computational-rd/vaal-manual

A polymorphism discovery algorithm for short reads. To run it, you provide reads (and quality scores) from a "sample genome" as input, along with a vector sequence to trim from the reads, and a reference sequence for a related genome to compare to. VAAL produces as output a an assembly for the sample genome, together with a mask showing which bases are "trusted". It then deduces from that a list of differences between the sample and related genomes. Alternatively, it can be provided as input read data for two sample genomes, together with a reference sequence for a related genome. In this case, VAAL produces assemblies for each of the sample genomes, and compares them to each other, thereby deducing a list of differences between them. VAAL has been tested on bacteria, using single lanes of 36 bp unpaired reads from the Illumina platform. Note: This software package is no longer supported and information on this page is provided for archival purposes only.

Proper citation: VAAL (RRID:SCR_001184) Copy   

•   Source: SciCrunch Registry

http://bionimbus.opensciencedatacloud.org/

A cloud-based infrastructure for managing, analyzing and sharing genomics datasets.

Proper citation: Bionimbus (RRID:SCR_001189) Copy   

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

Software program suitable for genome-scale data which uses a Markov-hidden Markov model (MHMM) to estimate local ancestry. The MHMM makes it possible to identify genomic blocks of a particular ancestry by use of any high-density single-nucleotide-polymorphism panel. One application is to perform admixture mapping without genotyping special ancestry-informative-marker panels.

Proper citation: SABER (RRID:SCR_001257) Copy   

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

Software package for non-parametric bootstrap and permutation resampling-based multiple testing procedures (including empirical Bayes methods) for controlling the family-wise error rate (FWER), generalized family-wise error rate (gFWER), tail probability of the proportion of false positives (TPPFP), and false discovery rate (FDR). Several choices of bootstrap-based null distribution are implemented (centered, centered and scaled, quantile-transformed). Single-step and step-wise methods are available. Tests based on a variety of t- and F-statistics (including t-statistics based on regression parameters from linear and survival models as well as those based on correlation parameters) are included. When probing hypotheses with t-statistics, users may also select a potentially faster null distribution which is multivariate normal with mean zero and variance covariance matrix derived from the vector influence function. Results are reported in terms of adjusted p-values, confidence regions and test statistic cutoffs. The procedures are directly applicable to identifying differentially expressed genes in DNA microarray experiments.

Proper citation: multtest (RRID:SCR_001255) Copy   

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https://github.com/pmelsted/BFCounter

Software program for counting k-mers in DNA sequence data. It identifies all the k-mers that occur more than once in a DNA sequence data set using a Bloom filter, a probabilistic data structure that stores all the observed k-mers implicitly in memory with greatly reduced memory requirements.

Proper citation: BFCounter (RRID:SCR_001248) Copy   

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http://www.zbh.uni-hamburg.de/?id=211

A collection of flexible and memory-efficient software programs for k-mer counting and indexing of large sequence sets. It is based on enhanced suffix arrays which gives a much larger flexibility concerning the choice of the k-mer size. It can process large data sizes of several billion bases.

Proper citation: TALLYMER (RRID:SCR_001244) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/release/bioc/html/quantsmooth.html

Software package for quantile smoothing and genomic visualization of array data.

Proper citation: quantsmooth (RRID:SCR_001271) Copy   

•   Source: SciCrunch Registry

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   

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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   

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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/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/macat.html

Software library that contains functions to investigate links between differential gene expression and the chromosomal localization of the genes. It is motivated by the common observation of phenomena involving large chromosomal regions in tumor cells. MACAT is the implementation of a statistical approach for identifying significantly differentially expressed chromosome regions.

Proper citation: MACAT (RRID:SCR_001350) Copy   

•   Source: SciCrunch Registry

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

Software to identify differentially expressed genes. A hierarchical Bayesian approach is used, and the hyperparameters are estimated using empirical Bayes.

Proper citation: lapmix (RRID:SCR_001347) 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   

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

Software package to test for differentially expressed genes with microarray data. It can be used with both cDNA microarrays or Affymetrix chip. The packge fits a robust Bayesian hierarchical model for testing for differential expression. Outliers are modeled explicitly using a $t$-distribution. The model includes an exchangeable prior for the variances which allow different variances for the genes but still shrink extreme empirical variances. The model can be used for testing for differentially expressed genes among multiple samples, and can distinguish between the different possible patterns of differential expression when there are three or more samples. Parameter estimation is carried out using a novel version of Markov Chain Monte Carlo that is appropriate when the model puts mass on subspaces of the full parameter space.

Proper citation: bridge (RRID:SCR_001343) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/release/bioc/html/aroma.light.html

Light-weight software package for normalization and visualization of microarray data using only basic R data types. Software can be used standalone, be utilized in other packages, or be wrapped up in higher-level classes.

Proper citation: aroma.light (RRID:SCR_001312) Copy   

•   Source: SciCrunch Registry

http://www.bioconductor.org/packages/2.13/bioc/html/BeadDataPackR.html

Software that provides functionality for the compression and decompression of raw bead-level data from the Illumina BeadArray platform.

Proper citation: BeadDataPackR (RRID:SCR_001310) Copy   

•   Source: SciCrunch Registry