<?xml version="1.0" encoding="utf-8" standalone="yes"?><rss version="2.0" xmlns:atom="http://www.w3.org/2005/Atom"><channel><title>Tools |</title><link>https://cgm.uni-frankfurt.de/tools/</link><atom:link href="https://cgm.uni-frankfurt.de/tools/index.xml" rel="self" type="application/rss+xml"/><description>Tools</description><generator>HugoBlox Kit (https://hugoblox.com)</generator><language>en-us</language><lastBuildDate>Sun, 19 May 2024 00:00:00 +0000</lastBuildDate><image><url>https://cgm.uni-frankfurt.de/media/logo.svg</url><title>Tools</title><link>https://cgm.uni-frankfurt.de/tools/</link></image><item><title>AtlasLens</title><link>https://cgm.uni-frankfurt.de/tools/atlaslens/</link><pubDate>Fri, 17 May 2024 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/atlaslens/</guid><description>&lt;p&gt;TODO: add description and logo&lt;/p&gt;</description></item><item><title>MetaFR</title><link>https://cgm.uni-frankfurt.de/tools/metafr/</link><pubDate>Fri, 17 May 2024 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/metafr/</guid><description>&lt;p&gt;TODO: add description and logo&lt;/p&gt;</description></item><item><title>RANKOR</title><link>https://cgm.uni-frankfurt.de/tools/rankor/</link><pubDate>Fri, 17 May 2024 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/rankor/</guid><description>&lt;p&gt;TODO: add description and logo&lt;/p&gt;</description></item><item><title>SNEEP</title><link>https://cgm.uni-frankfurt.de/tools/sneep/</link><pubDate>Fri, 17 May 2024 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/sneep/</guid><description>&lt;p&gt;SNEEP is a statistical approach to predict the effect of non-coding genetic variants on transcription factor (TF) binding sites. It scales to large genomic datasets and can integrate cell type specific genetic and epigenetic information such as open chromatin or expression data to prioritize functional non-coding variants. Further, by linking variants to target genes via enhancer-gene interactions, SNEEP enables mechanistic interpretation of genetic associations.&lt;/p&gt;</description></item><item><title>FAME</title><link>https://cgm.uni-frankfurt.de/tools/fame/</link><pubDate>Fri, 16 Jun 2023 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/fame/</guid><description>&lt;p&gt;FAME is a software for the alignment and direct quantification of CpG methylation values from whole genome bisulfite sequencing. Different to other established methods, it does not produce intermediate aligment files and uses new index structures to be fast.&lt;/p&gt;</description></item><item><title>STARE</title><link>https://cgm.uni-frankfurt.de/tools/stare/</link><pubDate>Sat, 11 Sep 2021 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/stare/</guid><description>&lt;p&gt;STARE is a framework that combines two tasks, which can also work independently:&lt;/p&gt;
&lt;ul&gt;
&lt;li&gt;Score enhancer-gene interactions with the generalized Activity-By-Contact (gABC) model. It uses a measurement of enhancer activity and optionally also chromatin contact data.&lt;/li&gt;
&lt;li&gt;Derive TF affinities for regions.&lt;/li&gt;
&lt;/ul&gt;
&lt;p&gt;Those two parts are combined to summarise TF affinities on gene level, which allows for a variety of downstream analyses. It can be applied to pseudobulked single-cell data as well.&lt;/p&gt;</description></item><item><title>STITCHIT</title><link>https://cgm.uni-frankfurt.de/tools/stitchit/</link><pubDate>Sat, 11 Sep 2021 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/stitchit/</guid><description>&lt;p&gt;STITCHIT is a software for learning gene-specific regulatory elements from paired epigenomics and expression data.&lt;/p&gt;</description></item><item><title>EpiRegio</title><link>https://cgm.uni-frankfurt.de/tools/epiregio/</link><pubDate>Thu, 02 Jul 2020 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/epiregio/</guid><description>&lt;p&gt;EpiRegio is a resource of Regulatory EleMents (REMs), non-coding DNA regions that are predicted to regulate the expression of their target genes. It hosts 2.4 millions of such elements for the human genome and provides cell-type specific expression and activity parameters for each of the elements. It supports different searches and allows batch queries using a REST API.&lt;/p&gt;</description></item><item><title>ORNA</title><link>https://cgm.uni-frankfurt.de/tools/orna/</link><pubDate>Tue, 26 Mar 2019 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/orna/</guid><description>&lt;p&gt;ORNA is a read normalization (reduction) software. That allows to remove redudancy in large NGS datasets, with as little effect as possible on downstream assembly approaches.&lt;/p&gt;</description></item><item><title>TEPIC</title><link>https://cgm.uni-frankfurt.de/tools/tepic/</link><pubDate>Mon, 28 Nov 2016 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/tepic/</guid><description>&lt;p&gt;TEPIC is a software package for integrative analysis of open-chromatin datasets for TF binding affinity prediction. It can be combined with gene annotation to provide gene-level estimates of TF regulation.&lt;/p&gt;</description></item><item><title>KREATION</title><link>https://cgm.uni-frankfurt.de/tools/kreation/</link><pubDate>Thu, 28 Apr 2016 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/kreation/</guid><description>&lt;p&gt;KREATION is meta-software that enables parameter selection for de novo transcriptome assemblers. It also has a missassembly filter that can be used to improve the quality of assemblies.&lt;/p&gt;</description></item><item><title>Fiona</title><link>https://cgm.uni-frankfurt.de/tools/fiona/</link><pubDate>Fri, 22 Aug 2014 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/fiona/</guid><description>&lt;p&gt;Fiona is a genome read error correction method that corrects indel and substitution errors using several word lengths. It automatically adapts the parameters to the data and supports OpenMP parallelization.&lt;/p&gt;</description></item><item><title>SEECER</title><link>https://cgm.uni-frankfurt.de/tools/seecer/</link><pubDate>Wed, 03 Apr 2013 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/seecer/</guid><description>&lt;p&gt;SEquencing Error CorrEction for RNA sequencing data (SEECER) is a read error correction method designed for non-uniform sequencing data sets, in particular RNA-seq. It clusters reads and reconstructs profile HMMs to correct indel and substitution errors with high sensitivity.&lt;/p&gt;</description></item><item><title>DREM 2.0</title><link>https://cgm.uni-frankfurt.de/tools/drem2/</link><pubDate>Thu, 16 Aug 2012 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/drem2/</guid><description>&lt;p&gt;DREM is a input/output HMM based method to reconstruct dynamic maps of TF regulation using expression time series data. The software is written in Java and has a rich user interface for network display and downstream analyses.&lt;/p&gt;</description></item><item><title>Oases</title><link>https://cgm.uni-frankfurt.de/tools/oases/</link><pubDate>Fri, 24 Feb 2012 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/oases/</guid><description>&lt;p&gt;Oases is a de novo transcriptome assembler that exploits similarities between de Bruijn graphs and splicing graphs to reconstructs full length mRNAs from RNA-Seq data with high sensitivity and is one of the most widely used methods in its class.&lt;/p&gt;</description></item><item><title>ALF</title><link>https://cgm.uni-frankfurt.de/tools/alf/</link><pubDate>Thu, 12 Jan 2012 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/alf/</guid><description>&lt;p&gt;ALF is a toolbox of alignment-free sequence similarity measures, including a new measure, N2, that includes mismatches and the reverse complement of words. We have shown that N2 outperforms other common alignment-free measures in performance and runtime, it was desinged to accomodate inexact overlaps as in degenerate binding sites or reads with sequencing errors.&lt;/p&gt;</description></item><item><title>SplazerS</title><link>https://cgm.uni-frankfurt.de/tools/splazers/</link><pubDate>Wed, 11 Jan 2012 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/splazers/</guid><description>&lt;p&gt;SplazerS is a split-read indel alignment method with high sensitivity that works for single and paired-end reads.&lt;/p&gt;</description></item><item><title>Phenomizer</title><link>https://cgm.uni-frankfurt.de/tools/phenomizer/</link><pubDate>Fri, 09 Oct 2009 00:00:00 +0000</pubDate><guid>https://cgm.uni-frankfurt.de/tools/phenomizer/</guid><description>&lt;p&gt;The Phenomizer is an online webservice for clinical diagnosis. The physician can can query the database to get predictions of the best matching disease for a set of observed phenotypes.&lt;/p&gt;</description></item></channel></rss>