Cluster samples to find expressed sequences and sequence families or compare multiple samples to look for enrichment in panning or immunization experiments. Clustering may also be used for spotting positional differences in affinity maturation experiments and other hotspots.
Define your own clonotype
Use advanced clustering options to define your own clonotypes whether that is a single region or a mix of annotated regions and germline genes. It is even possible to cluster across both antibody heavy and light chains for natively paired sequences giving a unique clonotype assignment.
- Powerful clustering algorithms enable you to cluster on multiple regions such as CDRs and FRs across heavy/light/kappa chains. Additionally, it is possible to cluster on one or more germline genes too.
- Clustering on germline gene AND sequence region may give multiple clonal groups with different v-gene and identical CDR-H3’s.
- Clustering using both CDR-H2 and CDR-H3 may reveal correlations between these two regions which are not found otherwise.
- Easily count number of unique sequences and regions in the entire dataset.
- Examine sequence diversity in samples and individual clusters.
- Include cluster counts and diversity in alignment views for visualization of most expressed sequences.
A picture is worth a thousand words
Charts give you a quick overview of your data. This can be showing largest clusters but also diversity in your data.
- Multiple different chats showing cluster size, diversity etc.
- Charts are interactive making it easy to filter on the data you want!
Compare tens of millions of reads
Look for sequence enrichment during panning rounds or just find overlap in sequence space between multiple samples. Additionally, use the comparison tool to deep mine large NGS repertoires for good bindes by use of well characterized sanger sequences as seed sequence.
- Compare tens of samples and look for enrichments in panning experiments.
- Use well characterized sanger sequences to mine NGS repertoires for good binders.
- Find overlap in sequence space between samples.
Mine NGS repertoires with Sanger sequences
Use well characterized Sanger sequences as “seed” for clustering to find similar sequences in large repertoire studies with tens of millions of NGS reads. This can reveal untapped value in sort of naturally occurring antibodies with similar characteristics as already known antibodies. This may enable an easier route to new patents with less manual protein and antibody engineering work.
- Mine your NGS data to find novel binders.
- With and without using Sanger sequences as seed sequence.
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