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http://www.stat.brown.edu/ZWU/research.aspx

Borrows information across sequences to establish prior distribution of sample variation, so that biological variation can be accounted for even when replicates are not available.

Proper citation: ASC (RRID:SCR_001013) Copy   

•   Source: SciCrunch Registry

https://code.google.com/p/jmzml/

A Java application programming interface (API) for the Proteomics Standards Initiative mzML data standard.

Proper citation: jmzML (RRID:SCR_001119) Copy   

•   Source: SciCrunch Registry

http://bioconductor.org/packages/devel/bioc/html/massiR.html

Software that predicts the sex of samples in gene expression microarray datasets.

Proper citation: massiR (RRID:SCR_001157) Copy   

•   Source: SciCrunch Registry

http://www.ebi.ac.uk/~stijn/reaper/reaper.html

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23, 2022. Software program for demultiplexing, trimming and filtering short read sequencing data.

Proper citation: Reaper - Demultiplexing trimming and filtering sequencing data (RRID:SCR_001144) Copy   

•   Source: SciCrunch Registry

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

Software package for quality control of Affymetrix GeneChip expression data and reproducibility analysis of human whole genome chips with the MAQC reference datasets.

Proper citation: yaqcaffy (RRID:SCR_001295) Copy   

•   Source: SciCrunch Registry

http://montgomerylab.stanford.edu/spliceplot/index.html

A software tool for visualizing alternative splicing and the effects of splicing quantitative trait loci (sQTLs) from RNA-seq data. It provides a simple command line interface for drawing sashimi plots, hive plots, and structure plots of alternative splicing events from .bam, .gtf, and .vcf files.

Proper citation: SplicePlot (RRID:SCR_001172) Copy   

•   Source: SciCrunch Registry

http://julian-gehring.github.io/les/

THIS RESOURCE IS NO LONGER IN SERVICE. Documented on September 23,2022. Software package that estimates Loci of Enhanced Significance (LES) in tiling microarray data. These are regions of regulation such as found in differential transcription, CHiP-chip, or DNA modification analysis. The package provides a universal framework suitable for identifying differential effects in tiling microarray data sets, and is independent of the underlying statistics at the level of single probes.

Proper citation: les (RRID:SCR_001291) Copy   

•   Source: SciCrunch Registry

http://qualimap.bioinfo.cipf.es/

Software application written in Java and R that provides both a Graphical User Inteface (GUI) and a command-line interface to facilitate the quality control of alignment sequencing data. It examines sequencing alignment data in SAM / BAM files according to the features of the mapped reads and provides an overall view of the data that helps to the detect biases in the sequencing and/or mapping of the data and eases decision-making for further analysis.

Proper citation: QualiMap (RRID:SCR_001209) Copy   

•   Source: SciCrunch Registry

http://pathology.wustl.edu/VirusHunter/

A fully automated and modular software package for mining sequence data to identify sequences of microbial origin. The pipeline was optimized for analysis of data generated by the Roche/454 next-generation sequencing platform but can be applied to longer sequences (Sanger sequencing data or assembled contigs) as well. Microbial sequences are identified on the basis of BLAST alignments and the taxonomic classification of the reference sequence(s) to which a read is aligned. Viruses are the focal point of VirusHunter as released, but it can be easily modified to generate parallel outputs for bacterial or parasitic species. To date, VirusHunter has been applied to thousands of specimens, including human, animal and environmental samples, resulting in the detection of many known and novel viruses.

Proper citation: VirusHunter (RRID:SCR_001198) Copy   

•   Source: SciCrunch Registry

http://www.biobase-international.com/product/genome-trax

Service that provides a comprehensive compilation of variant knowledge that allows you to identify pathogenic variants in human whole genome or exome sequences. It makes it easy to upload a complete genome?s worth of variations and identify the biologically relevant subset of known mutations, mutations that are novel and appear in a candidate disease genes, or mutations that are predicted to have a deleterious effect. The database includes a comprehensive collection of disease causing mutations from HGMD Professional, regulatory sites from TRANSFAC , and disease genes, drug targets and pathways from PROTEOME, as well as pharmacogenomic variants. It integrates the best public data-sets on somatic mutations, allele frequencies and clinical variants, in their most up-to-date version, for a total of more than 165 million annotations. It is possible to identify known pathogenic variants, remove harmless common variants, and obtain deleterious predictions for novel variants. With family data, it is possible to identify variants that are de novo, compound heterozygous only in the offspring. All of the results can be downloaded to Excel for further review. For core facilities and bioinformaticians, the complete underlying data is made available for download and easy integration into custom analysis pipelines. Genome Trax data is optimized to work with many other software packages, such as ANNOVARTM, CLC bio, Alamut, SimulConsult, and Cartagenia.

Proper citation: Genome Trax (RRID:SCR_001234) Copy   

•   Source: SciCrunch Registry

http://autosome.ru/ChIPMunk/

DNA motif discovery software adapted for ChIP-Seq data. It is an iterative algorithm that combines greedy optimization with bootstrapping and uses coverage profiles as motif positional preferences. It does not require truncation of long DNA segments and it is practical for processing up to tens of thousands of data sequences

Proper citation: ChIPMunk (RRID:SCR_001191) Copy   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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

Out of 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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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   

•   Source: SciCrunch Registry

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