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Galaxy / Rätsch Lab
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Tools
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UCSC Main
table browser
EBI SRA
ENA SRA
Get Microbial Data
BioMart
Ensembl server
CBI Rice Mart
rice mart
GrameneMart
Central server
modENCODE fly
server
Flymine
server
modENCODE modMine
server
MouseMine
server
Ratmine
server
YeastMine
server
modENCODE worm
server
WormBase
server
Sequence Analysis
Toy Data
MotifGen (FASTA)
Generation of a sequence toy data set for motif discovery in FASTA format.
MotifGen (ARFF)
Generation of a sequence toy data set for motif discovery in ARFF format.
CloudGen (ARFF)
Generation of a toy data set
SVM Toolbox
Train and Test SVMs
Train SVMs and predict for given hyper-parameters
Evaluate Predictions
Use predictions and labeled examples to measure prediction performance
SVM Model Selection
Find the best combination of SVM hyper-parameters
Positional Oligomer Matrices
Visualize SVMs with WD kernel
KIRMES
(0) Examples and Instructions
Instructions on how to use the KIRMES modular prediction and classification tools, including examples with predefined datasets.
(1) KIRMES K-Mer Counting
Find over-represented motifs using a k-mer counting strategy
(1) PRIORITY Gibbs Sampler
Find over-represented motifs using Raluca Gordan's PRIORITY program
(1) INCLUSive MotifSampler
Find over-represented motifs in a FASTA file
(2) Prepare Prediction Dataset
Find a set of motifs in a FASTA file
(3) KIRMES Training and Prediction
Trains KIRMES using a set of positive and negative regulatory regions
Genomic Signals
ARTS
Accurate transcription start site prediction
ASP
Accurate splice site prediction
NuPoP
Predict nucleosome positioning for DNA sequences of any length
Gene Finding
mGene.web (v0.4)
Examples and Instructions (v0.2)
Instructions on how to use the mGene monolithic tools and examples with predefined datasets
mGeneTrain (v0.2)
Trains mGene using set of known genes
mGenePredict (v0.2)
Predicts genes using a trained mGene system
mGeneEval (v0.2)
Computes performance measures based on gene labels and predictions
Oqtans (v0.1)
mGene.web modules (v0.4)
Examples and Instructions
Instructions on how to use the mGene tools with predefined datasets
GenomeTool
Creates a genome information object (GIO) from FASTA sequences
mGene_GFFParser
Generates an annotation gene structure object (AGS)
Anno2SignalLabel
Generates labeled positions from an annotation gene structure (AGS)
SignalTrain
Trains a signal predictor using a set of labeled positions
SignalPredict
Applies a trained signal predictor to the whole genome
SignalEval
Computes performance measures based on signal labels and predictions
Anno2ContentLabel
Generates labeled content segments from an annotation
ContentTrain
Trains a content predictor using a set of labeled segments
ContentPredict
Applies a trained content predictor to the whole genome
ContentEval
Computes performance measures based on content (segment) labels and predictions
GeneTrain
Trains mGene using set of known genes and signal predictions
GenePredict
Genome-wide gene prediction using the trained mGene system
GeneEval
Computes performance measures based on gene labels and predictions
ComposeMGenePredictor
Creates a complete mGene predictor object from the various parts
Read Mapping
Unspliced Alignment
Bowtie2
is a short-read aligner
Map with BWA for Illumina
Map with GenomeMapper
Spliced Alignment
Map with PALMapper
Tophat for Illumina
Find splice junctions using RNA-seq data
Tophat2
Gapped-read mapper for RNA-seq data
STAR
RNA-seq read mapper
ASP
Accurate splice site prediction
Transcript Prediction/Assembly
mTIM (v0.2)
mTIM-Train
data preparation and training
Predict using mTIM
Genome-wide prediction with mTIM
Evaluate mTIM transcript predictions
Evaluation of mTIM transcript predictions
Trinity (r2013-08-14)
Trinity
De novo assembly of transcriptome from RNA-Seq data
Scripture
Scripture
ab initio transcriptome reconstruction from RNA-Seq reads
Cufftools (v2.1.1)
Cufflinks
transcript assembly and FPKM estimates for RNA-Seq data
Cuffcompare
compare assembled transcripts to a reference annotation and track Cufflinks transcripts across multiple experiments
Cuffmerge
merge together several Cufflinks assemblies
Differential/Quantitative Analysis
rQuant
Determines transcript abundance from read alignments
rDiff
Determines differentially expressed transcripts from read alignments
DESeq
Determines differentially expressed transcripts from read alignments
DESeq2
Differential gene expression analysis based on the negative binomial distribution
DEXSeq
Inference of differential exon usage in RNA-Seq
edgeR
Empirical analysis of digital gene expression data in R
Cuffdiff
find significant changes in transcript expression, splicing, and promoter use
RiboDiff
Detect protein translational efficiency difference
Enrichment Analysis (v0.1)
topGO
Enrichment analysis for Gene Ontology
GeneSetter
plots family of diff. or not or expressed genes
Genetics Tools
Read Alignment Filtering (v0.2)
SAFT
Simple Alignment Filtering Tool
MMR
Multiple Mapper Resolution
NGS Tools
GFF Toolkit (v0.1)
Grooming Programs
Examine_GFF
file Parent-Child relations
FeatureScan
gives an overview about GFF feature content
Converter Programs
GTF_to_GFF3
converter
BED_to_GFF3
converter
GBK-to-GFF
converter
SInBaD Tools
SInBaD
Exploring functional variant discovery in non-coding regions
NGS: Mapping
Map with BFAST
Map with PerM
for SOLiD and Illumina
Re-align with SRMA
Map with Mosaik
NGS: QPALMA Tools
Artificial Data
Random subset of FASTQ
Create error model
Artificial spliced reads from GFF and Fastq
SplicePredict (v0.2)
Predicts splice sites on the whole genome
Training
Train QPALMA
Alignment
Map with PALMapper
NGS: mTIM Transcript Prediction
Reconstruction
Examples and Instructions
Instructions on how to use the mTIM tools and examples with predefined datasets
Predict using mTIM
Genome-wide prediction with mTIM
Detect isoforms using SplAdder
Detection of new RNA-seq confirmed isoforms with SplAdder
Infer ORFs using SplAdder
Inference of Open Reading Frames using InferORF
Evaluate mTIM transcript predictions
Evaluation of mTIM transcript predictions
Other Tools
NGS: Evaluation
Compare to Optimal Alignment
Analyze Error Model
Analyze Alignment Error
NGS: Alignment Filtering
SAFT
Simple Alignment Filtering Tool
Convert Formats
AXT to concatenated FASTA
Converts an AXT formatted file to a concatenated FASTA alignment
AXT to FASTA
Converts an AXT formatted file to FASTA format
AXT to LAV
Converts an AXT formatted file to LAV format
BED-to-GFF
converter
GFF-to-BED
converter
LAV to BED
Converts a LAV formatted file to BED format
MAF to BED
Converts a MAF formatted file to the BED format
MAF to Interval
Converts a MAF formatted file to the Interval format
MAF to FASTA
Converts a MAF formatted file to FASTA format
Wiggle-to-Interval
converter
SFF converter
GTF-to-BEDGraph
converter
Wig/BedGraph-to-bigWig
converter
BED-to-bigBed
converter
Text Manipulation
Add column
to an existing dataset
Concatenate datasets
tail-to-head
Cut
columns from a table
Merge Columns
together
Convert
delimiters to TAB
Create single interval
as a new dataset
Change Case
of selected columns
Paste
two files side by side
Remove beginning
of a file
Select random lines
from a file
Select first
lines from a dataset
Select last
lines from a dataset
Trim
leading or trailing characters
Line/Word/Character count
of a dataset
Secure Hash / Message Digest
on a dataset
Join, Subtract and Group
Join two Datasets
side by side on a specified field
Compare two Datasets
to find common or distinct rows
Group
data by a column and perform aggregate operation on other columns.
Filter and Sort
Filter
data on any column using simple expressions
Sort
data in ascending or descending order
Select
lines that match an expression
GFF
Extract features
from GFF data
Filter GTF data by attribute values_list
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