Bulk Omics

Transcriptomics and Immune Repertoire (TCR & BCR)

Bulk Immune Repertoire

Bulk TCRseq & BCRseq BCR

Pre Processing & Standard Analysis

Relying on 15 years of research, our regular immune repertoire analysis at Parean are not the common ones available.

After QC and preprocessing, we provide descriptive gene and diversity profiles, spectra typing analysis or repertoire sharing analysis

Pre Processing

QC, Normalisation, Filtration, Alignment of sequences to a reference repertoire,
Clonotype identification and counting,
QC & Somatic hypermutations (SHMs) identification (Only for BCR).

Deliverables

Tables including count data in MiAIRR format.

Standard Analysis

Descriptive gene usage (V, J & V-J),

Descriptive diversity profiles (Richness, Shannon entropy, Mean clonal frequency),

Spectratyping analysis (CDR3 length distributions),

Repertoire sharing analysis (clonal overlap).

Deliverables

Tables including count data in MiAIRR format & Graphs, meeting with our team.

Advanced Analysis

We master cutting-edge immune repertoire analysis, powered by AI.

Dive into the best analysis and representation such diversity metrics, repertoire sharing analysis, clonal architecture, generation probability and clonal specificity, in silico repertoire simulation or public datasets checking.

Advanced Analysis

Differential gene usage (V, J and VJ),
Diversity metrics (Rényi entropy, Chao, Polyclonal Monoclonal Diversity Index),
Spectratyping perturbation analysis. Signature identification,
Repertoire sharing analysis (Morisita-horn, Jaccard, Jensen–Shannon divergence index),
Clonal architecture (Networks, K-mers),
Physicochemical properties. Immunoglobulin Phylogenetic analysis (only BCR),
Repertoire classification,
Generation probability inference,
Clonal specificity inference,
Simulation in silico repertoire.

Deliverables

Bioinformatics object, complemented by the analyses listed above and relevant graphs

Bulk Transcriptomics

Bulk RNAseq

Pre Processing & Standard Analysis

Your time is precious, and so are your samples. Our regular transcriptomics protocols enables robust and fast analysis of gene expression, trimming if needed, exploratory analysis and relevant graphical representation.

Pre processing

Raw Data QC, Trimming if needed, Alignment on latest reference genome, Quantification of sequences into count data.

Deliverables

Fastq; QC report; Raw count data and meeting with our team.

Standard Analysis

Data transformation and normalisation, Exploratory Analysis & Filtration.

Deliverables

Normalized data; Integrated sample data; Exploratory analysis figures (+Fastq; QC report; Raw count data); meeting with our team.

Advanced Analysis

Go beyond regular analysis, and use our methods for batch effect correction, and use relevant methods such as Over Representation Analysis, Gee Set analysis (public or specific signature), differential gene expression, HLA typing…

Advanced Analysis

Batch effect correction (if necessary),
Differential gene expression analysis and HLA typing detection,
ORA analysis (Over Representation Analysis): Functional analysis of differentially expressed genes (eg pathways with KEGG, Ontologies with GO),
GSA analysis (gene set analysis): Statistical analysis of gene sets (pathways, ontologies, predefined molecular signatures). This analysis consists of testing the differential expression of previously defined sets of genes (eg using KEGG, GO, Broad Institute MsigDB, …).

Deliverables

Graphical representation; meeting with our team (+ standard analysis deliverables).