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ChIP-seq
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Microarray
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ChIP-seq
Gene-list Analysis
Microarray
RMaNI
RNA-seq
WGCNA
Home
Microarray
Please enter a short name for your analysis.:
Microarray Data Import
Select data import option.
Input Type:
onlineimport
celfiles
procdata
Please enter the NCBI GEO accession number for the dataset. We support GSE and GDS datasets, so accession must start from GSE or GDS e.g. GSE14407 or GDS3592.:
Upload a Zip file:
Please upload zip file containing all the celfiles.
Please select data normalisation method.:
mas5
rma
gcrma
plier
dChip
Please upload a file containing processed data. File must be in a csv format with headers. Format - first row=probes then columns=samples.
Select chip type:
hgu133a
hgu133a2
hgu133b
hgu133plus2
hgu219
hgu95a
hgu95av2
hgu95b
hgu95c
hgu95d
hgu95e
hthgu133a
hthgu133b
Upload sample annotation file:
Please upload a sample annotation file. File must be in csv format with column headers. First column name must be sample names as in the data file and second column name must be the condition (like normal/cancer etc).
Select top genes (optional)
Select top genes using either highest average expression or maximum coefficient of variation of genes across all samples.
maxCoefVariation
maxAverageExpression
Please select the selectGenesMethod for selecting top genes in the dataset.
50
100
200
500
1000
2000
4000
Differential Gene Expression Analysis
Perform differential gene expression data analysis.
Please select differential gene expression detection method.:
LIMMA
SAM
Analysis of differentially expressed genes (optional)
Perform trend analysis using JT test - Jonckheere-Terpstra test.
Regulatory Impact Factors (RIF) Analysis
Signalling Pathway Impact Analysis
Broad gene set analysis.
Select the geneset for Broad geneset analysis.:
c1.positional
c2.allcurated
c2.cgp
c2.allcp
c2.cpbiocarta
c2.cpkegg
c2.cpreactome
c3.allmotif
c3.micrornatargets
c3.tftargets
c4.allcomputational
c4.cgn
c4.cancermodules
c5.allgo
c5.bp
c5.cc
c5.mf
Cancer Outlier Profile Analysis (COPA).
modified Cancer Outlier Profile Analysis (mCOPA)
Select percentile value for mCOPA.:
90
95
Gene regulatory network inference.
Please select GRN inference method.:
rn
mrnet
clr
aracne
pcit
genie
Compare feature selection and clustering methods.
Gene-list Analysis Framework
Functional enrichmnent analysis using DAVID
Druggability analysis using CancerResource
Functional annotation of genes using gProfileR
Functional annotation of genes using EDanalysis
Gene Enrichment Disequilibrium Analysis using EDanalysis for BP
Gene Enrichment Disequilibrium Analysis using EDanalysis for MF
Gene Enrichment Disequilibrium Analysis using EDanalysis for CC
Promoter analysis
Select the upstream region:
500
1000
2000
5000
Select the downstream region:
50
100
200
Extract the promoter sequences for the input genes
Detect CpG islands in the promoter sequences of the input genes
Remove sequences with over GC content in the promoter sequences of the input genes. (>55% GC content for human)
Submit the input genes to MEME Suite of tools for Motif Discovery, Motif Comparison and Motif Enrichment Analysis
Perform TFBS over-representation analysis using oPOSSUM