Search Results for "seq"
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Showing 15 open source projects for "seq"
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FastQC
A quality control analysis tool for high throughput sequencing data
... then direct you to where your data may have problems and allow you to take necessary steps to correct it before doing any further analysis. FastQC is not tied to any specific type of sequencing technique, so it can be used to look at libraries of various experiment types (Genomic Sequencing, ChIP-Seq, RNA-Seq, BS-Seq etc etc). -
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BBMap
BBMap short read aligner, and other bioinformatic tools.
This package includes BBMap, a short read aligner, as well as various other bioinformatic tools. It is written in pure Java, can run on any platform, and has no dependencies other than Java being installed (compiled for Java 6 and higher). All tools are efficient and multithreaded. BBMap: Short read aligner for DNA and RNA-seq data. Capable of handling arbitrarily large genomes with millions of scaffolds. Handles Illumina, PacBio, 454, and other reads; very high sensitivity... -
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COHCAP
City of Hope CpG Island Analysis Pipeline
COHCAP (City of Hope CpG Island Analysis Pipeline, pronounced "co-cap") is an algorithm to analyze single-nucleotide resolution methylation data (Illumina 450k methylation array, targeted BS-Seq, etc.). Please note: 1) The SourceForge version of COHCAP is no longer being updated. Please see the GitHub version: https://github.com/cwarden45/COHCAP This was the source repository for the Bioconductor version, with some changes after the decision to only provide the code through GitHub... -
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HSRA
Hadoop spliced read aligner for RNA-seq data
HSRA is a MapReduce-based parallel tool for mapping reads from RNA sequencing (RNA-seq) experiments. RNA-seq analyses typically begin by mapping reads to a reference genome in order to determine the location from which the reads were originated, which is a very time-consuming step. This tool allows bioinformatics researchers to efficiently distribute their mapping tasks over the nodes of a cluster by combining a fast multithreaded spliced aligner (HISAT2) with Apache Hadoop, which... -
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BisSNP
Bisulfite-seq/NOMe-seq SNPs & cytosine methylation caller
Now in Github: https://github.com/dnaase/Bis-tools/tree/master/Bis-SNP BisSNP is a package based on the Genome Analysis Toolkit (GATK) map-reduce framework for genotyping in bisulfite treated massively parallel sequencing (Bisulfite-seq, NOMe-seq and RRBS) on Illumina platform. It uses bayesian inference with either manually specified or automatically estimated methylation probabilities of different cytosine context(not only CpG, CHH, CHG in Bisulfite-seq, but also GCH et.al. in other... -
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Jafaran
Fast and more random implementations of java.util.Random.
Jafaran (Java Fast Random) provides fast, and for some more random, implementations of java.util.Random, with additional nextXXX() methods, and methods to retrieve and restore state. The names of implementations contain "Conc" (for concurrent) if they are thread-safe and non-blocking, or "Seq" (for sequential) if they are not thread-safe. Also provides an implementation of Ziggurat algorithm (based on J. A. Doornik paper, 2005), used by nextGaussian() methods of the provided... -
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came
Identification of chromatin accessibility from NOMe-seq
Chromatin accessibility plays a key role in epigenetic regulation of gene activation and silencing. Open chromatin regions allow regulatory elements such as transcription factors and polymerases to bind for gene expression while closed chromatin regions prevent the activity of transcriptional machinery. Recently, nucleosome occupancy and methylome sequencing (NOMe-seq) has been developed for simultaneously profiling of chromatin accessibility and DNA methylation on single molecules. However... -
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iMir
Integrated pipeline for HT miRNA-Seq data analysis
Processing of smallRNA-Seq data to gather biologically relevant information requires application of multiple statistical and bioinformatics tools from different sources, each focusing on a specific step of the analysis pipeline. The analytical workflow can be challenging for the continuous interventions by the operator, a critical factor when large numbers of datasets need to be analyzed at once. To allow a flexible and comprehensive analysis of smallRNA-Seq data we designed a novel modular... -
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Deem
Analyze time-course data with significance tests, clustering, modeling
Use statistical methods to analyze time-course data (gene expression microarray and RNA-seq data in particular, but not limited to). Apply significance tests to filter out only significant genes or time series. Cluster time series into similar groups. Generate network models, including linear or non-linear models. Variable selection and optimization routines included. Written in Scala and R. The application is a cross-platform desktop app with a simple GUI and is fully functional... -
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This package contains code for use with Short Read DNA Sequencing technologies, and includes packages for ChIP-Seq, Whole Transcriptome Shotgun Sequencing, Whole Genome Shotgun Sequencing, SNP Detection, Transcript expression and file conversion.
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TFAST
Software for analysis of afSELEX-seq data
Transcription Factor Analysis using SELEX with High-Throughput Sequencing (TFAST) is software developed by the Mobley lab at the University of Michigan designed to assist with transcription factor binding site discovery using data generated from aptamer-free SELEX-seq (afSELEX-seq). -
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Seurat
A sequence analysis tool for normal/tumor DNA and RNA data.
THIS IS NO LONGER THE HOME FOR SEURAT. PLEASE GO TO https://sites.google.com/site/seuratsomatic/ --- Seurat is an sequence analysis program for somatic mutation and allelic imbalance discovery in paired tumor and normal genome and transcriptome data. -
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The Java class library, that contains classes for calculation of different mathematical relations between object and number sequences and sets: Kendall distance, Spearman distance, similarity measure, L1 distance and others.
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DawgPack is an ultra-fast, Cloud-based tool that maps many high coverage genomes and performs analysis to find clues for pathogenesis. It will integrate CNV, SNP, RNA-Seq and ChIP-Seq analyses.
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