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Synopis

ChiP (Chromatin-immunoprecipitation) is all about high quality antibodies, professional sample preparation and careful analysis of the resulting raw data (peaks). While for the wet-lab topics nothing has changed during the evolution from microarry ChIP assay to ChIP-Seq, the analysis part has changed to the better. This, because the data you obtain from modern NGS sequencers is just so much better than the one obtained by using microarray technology. However you still have to adapt your analysis workflow to the nature of your antibody and the resulting peaks. We are doing that by manually inspecting the results of each step of the analysis.

No result counts, if not presented in the best way. We are aiming for high-quality figures. We provide high-resolution images and additionally pdf versions of your graphics, which enable you to manipulate colors, text and many other options. Please see an example video here.

In case you want to contract it’s biology to analyze your ChIP-Seq project, we will divide the whole process into 4 steps, with you choosing which level of analysis you need:

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    Exerimental Design

    Consulting in the experimental design and technical procedure of the experiment. Sometimes one phone call can help tremendously.

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    Data preparation and alignment

    Heat our workstations: Data quality assessment, read manipulation (trimming, filtering) and alignment of your Chip-Seq reads.

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    Peaks: detection, annotation, filtering

    Peak calling with adjustment of the calling parameters after visual inspection of the result. Annotation with known genes/transcripts or other genomic features of interest (promoters, CpG islands …). Filtering of obtained enriched regions based on calling scores, p-values or location in respect to known genes/transcripts.

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    Transcription factor binding site analysis and biological interpretation.

    Starting from the list of called peaks we perform the detection of underlying binding motifs of transcription factors. This, for both know motifs from popular transcription factor binding site databases and also for not-known, new binding motifs. Biological interpretation includes Gene-ontology enrichment and Pathway involvement of the targeted genes of your transcription factor or integration with results from other assays.

We are analyzing Chip-Seq data from all mayor next-generation sequencers from Illumina or Ion-Torrent. We can start from files in FASTA, FASTQ, unaligned BAM files or SRA format.
We are not fixed to the usual suspects, like human, mouse or rat. Any species with a sequenced genome can be handled by us.

Please scroll down for more information about the single steps of our Chip-Seq workflow. Please contact us here, in case you have any question about our service. We are sure, that we can find a solution for any additional task, you might have in mind.
Please scroll down for more information about the single steps of our RNA-Seq workflow. Please contact us here, in case you have any question about our service.

Quality control, read preparation and alignment

Like for other NGS applications, also for ChIP-Seq quality assessment of the raw reads is crucial for successful analysis of any experiment. We are using widely used quality control tools like FASTQ for standard quality control and decision about filtering or trimming of raw reads. Additionally we apply ChIP-Seq specific control steps like fragment length estimation, which is important for general quality assessment and to decide the correct parameters for the later on peak calling. Alignment of Chip-Seq reads to the genome is maybe the least error-prone part in the workflow, however we always check alternatives, in case our standard aligner shows an unusual output. Before entering the next step of the workflow, we also visually inspect the aligned data (BAM files) in a genome browser.

Peaks: detection, annotation, filtering

Peak calling is the most crucial step of the workflow. Based on the results of the quality assessment, we carefully define the needed parameters needed for the peak calling algorithm. This step should, but does not have to contain a mock control (input or antibody control). During the step both the chip and the mock sample are normalized to each other. The resulting peak list is visually controlled on genome level for some hundred randomly selected peaks of the list. Please see the GIF animation on the right as an example for just 100 peaks. If everything looks fine, the initial list is filtered based on the p-values of the peaks and also on the number of reads per peak. We found some peak-caller overly optimistic, when using p-values alone. The final filtered list is then annotated with the genomic data base of your choice. This might be ENSEMBL, UCSC or any species specific genomic database. Finally the annotated list of peaks is used for biological interpretation and binding site analysis. In case you do have technical or biological replicates we can compare the lists. This might be a simple merge of two or more samples , more sophisticated logic (in sample1 AND in sample2) or in case of more biological replicates also statistical valuation of the results. You want to compare your results with similar public available samples. No problem at all.

Transcription factor binding site analysis and biological interpretation

We then analyse any underlying sequence pattern inheriting in the sequences of the peaks for possible transcription factor binding sites. This analysis is based on already known binding motifs of transcription factors from various database sources, but also a de-Novo motif search which allows the detection of not-known binding motifs. We summarize the obtained binding sites in regard to their genomic location (exonic, intronic, intergenic, Promoter…) and also in regard to the transcriptional start site of respective genes or transcripts. Besides, we are setting the results into the biological context. This can be an evaluation of over-representation of distinct biological relevant categories like Pathways or gene-ontolgy categories or an integration with additional available RNA-Seq data. You do have further ideas for continious processing of the results. Contact us, for sure we find a solution for your object.