Services
ChIP-Seq
We provide standard processing and quality assessment for single- and paired-end chip-seq data. More specific analysis are also available on demand. See below for details.
RNA-Seq
We provide standard processing and quality assessment for single- and paired-end rna-seq data. More specific analysis are also available on demand. See below for details.
ATAC-Seq
We provide standard processing and quality assessment for paired-end atac-seq data. More specific analysis are also available on demand. See below for details.
Details
ChIP-Seq
The processing of single- and paired-end data is currently provided through a galaxy workflow as requested by biologists.
You receive the following from us:
- QC (quality control)
- A multiqc report containing different metrics: single-end and paired-end.
- pca and samples correlation plots
- Fingerprint and coverage plots
- Signal
- Bam files
- bigwig files
- MACS2 peaks
- Analysis
- gene_ontologies
- Motifs detection
Further analysis
Custom plots and analysis can be provided within the framework of a collaboration. This includes but is not limited to:
- Heatmaps and clustering: K-mean, hierarchical, custom feature based, supervised clustering.
- Advanced motif analysis with ensembl methods.
- Gene ontologies with ChIPEnrich, clusterProfiler.
- Graphical analysis: Boxplots, violin plots, barplots, piecharts, etc.
- Differential binding analysis.
- Hidden markov modelling: Typically used to describe chromatin states.
- Linear regression analysis.
- Sub-group definition by venn diagram analysis.
- Refined peak calling with hiddenDomains, SICER, SPP, etc.
- Tissue specificity analysis.
RNA-Seq
The processing of single- and paired-end data is currently provided through a galaxy workflow as requested by biologists.
You receive the following from us:
- QC (quality control)
- A multiqc report containing different metrics: single-end and paired-end.
- Counts table: Raw and TPM Normalized counts from Salmon (transcriptome based) and Featurecounts (reference genome based)
- Correlation and PCA: Using no, CPM, RPKM and TPM normalization.
- Signal
- Bam files
- bigwig files: Using no, CPM, RPKM and TPM normalization.
Further analysis
Custom plots and analysis can be provided within the framework of a collaboration. This includes but is not limited to:
- Differential expression analysis with DEseq2 and/or EdgeR
- Heatmaps and clustering of differentially expressed genes.
- Gene ontologies of differentially expressed genes.
- Graphical analysis: Boxplots, violin plots, barplots, piecharts, etc.
ATAC-Seq