Interpretation
of Analysis
Data

Overview

Interpretation of
Repertoire Analysis Results

About Supplementary Material

TCR/BCR Repertoire Analysis

Overview

The results of the repertoire analysis are organized by genes. For TCR genes, two report files (Excel) are obtained for the TCRα chain and TCR β chain.

For BCR genes, two report files are also obtained for IgH chain and IgL chain. For IgH chain, a common report file is used for five kinds of H chains (IgM, IgG, IgA, IgD, and IgE),although IgH genes are independently amplified with different isotype-specific primers. As IgL genes (L chain) contain IgL and IgK, the report file is independently obtained for IgL and IgK. The genes corresponding to the report file are summarized.

Interpretation of Repertoire Analysis Results

An example of a report file is shown below.

  1. Report Type
    • Species and sample information in analysis request form
    • Report version
  2. Report Information
    • Date of report：The date when the report is created with our analysis system
    • Project ID：
    • Sample ID：ID represented as Sample ID plus gene
      (E.g., TCRα, β, γ, δ: a, b, c, d、
      BCR IgM, G, A, D, E, L, K: m, g, a, d, e, l, k)
  3. Sequence Information
    • Total reads：Total number of reads obtained from NGS
    • Assigned reads：Number of reads assigned to TCR genes
    • In frame reads：Number of reads with functional CDR3
    • Unique reads：Among “in-frame” reads, the number of reads with a unique combination of V-J genes and CDR3 amino acids (the species number of in-frame reads)
    • In frame / Unique：Average number of in-frame reads per unique read
  4. Diversity Indices
    • The diversity of the repertoire is described by several diversity indices. A greater score indicates higher diversity.
    • Shannon-Weaver index H’
      Shannon-Weaver index H’ is highly sensitive to low-frequency reads (unique reads of a small number) and suitable to describe repertoire diversity. Because of the sensitivity, low-frequency reads could dominantly affect the diversity index.
    • Inverse (Inv.) Simpson’s index 1/λ:Simpson’s index (reciprocal)
      In contrast to the Shannon-Weaver index, Inv. Simpson’s index is a diversity index with a feature that emphasizes high-frequency reads (unique reads that are very numerous). Because of this property, Inv. Simpson’s index 1/λ is appropriate to represent repertoire diversity with high-frequency reads.
    • Pielou’s evenness
      Pielou’s evenness refers to the level of similarity in the numbers of individuals between different species in a particular environment. The evenness of a community can be represented by Pielou’s evenness index. Mathematically, it is defined as a diversity index, a measure of biodiversity that quantifies how equal the members of a community are in terms of their numbers. Pielou’s evenness does not emphasize the specificity or diversity, but rather represents a diversity index that provides relatively stable values.
    • DE50（Diversity Evenness score）
      As an indicator of clonality (degree of cloning), DE50 describes, when the number of reads is summed up in rank order (from high to low), how many unique reads exist within 50% of in-frame reads. The lower the number is, the higher the clonality.
  5. Result of Repertoire Analysis (2D Graph)
    • The 2D bar graphs show the usage frequency of repertoire genes.
    • The x-axis indicates V or J genes. The y-axis indicates the frequency of each gene (%).
  6. Results of Repertoire Analysis (3D Graph)
    • The 3D bar graph displays the frequency of combinations of V gene segments and J gene segments.
    • The x-axis (width) and y-axis (depth) indicate J genes and V genes, respectively. The z-axis (height) stands for the frequencies of V-J combinations. The total of the frequencies is 100%.
    • Please note that a single bar may indicate multiple reads with the same V-J combination, but with different CDR3 sequences.
  7. Top 50 High-frequency Unique Reads
    • A unique read stands for a read with a particular combination of V-J-CDR3 in-frame. The top 50 unique reads are ranked in descending order of frequency
    • The table shows ranking, TRAV, TRAJ, CDR3 sequence, in-frame reads, and frequency of the reads (%) in this order.
    • Unique reads other than the top 50 reads are listed in a spreadsheet of the report Excel file, “back_data”

Note The Following When You Analyze Your Data

Owing to limitations of samples with a small number of cells, a tiny amount of RNA, or low quality of RNA or tissue, repertoire diversity may not be accurate for the samples. For these reasons, we strongly recommend the use of appropriate controls to ensure accurate comparison.

Tips on How to Read Repertoire Data　

1: Find characteristic patterns in the 3D graph.

  • Is any peak higher than the others?
  • Is the pattern similar to the others?

2: Select dominant clones (>1%) in the ranking table.

  • Identify as a candidate a clone that specifically responds to an antigen.

3: Compare diversity indices with controls.

  • Evaluate clonality

About Supplementary Material

In repertoire analysis, it is extremely laborious to compile and compare clones between specimens manually. Therefore, in our repertoire analysis, supplementary materials are provided to facilitate comparison of data in the same gene among multiple specimens.

  1. Sequence quality value (QV) score
  2. Comparison data for sequence information and diversity indices
  3. Comparison data for shared unique reads
  4. Updated gene names (Comparison with the name used before September 2017)

1: Sequence QV Score

  • Application:
  • Evaluate quality of sequence reads (R1, R2) for each sample.
  • Special attention should be paid when sequences with low QV (< « 20) are acquired.

Note: During paired-end sequencing with Illumina Miseq, the sequencing quality in R2 (reverse) decreases gradually. For that reason, the J gene and CDR3 sequence are determined with forward reads, while the V gene is determined with reverse reads. The data from R1 and R2 are automatically

2: Comparison Data for Sequence Information and Diversity indices

  • Application:
  • Confirm sequence information for each sample.Compare diversity indices between control sample and test sample(s).
  • Extract the diversity index from the table and carry out statistical analysis efficiently.

3: Comparison Data for Shared Unique Reads

  • Application:
  • Confirm unique reads for each sample without opening each file.
  • Find sequence reads shared between samples in one table and easily evaluate the dynamic change of the reads.
  • Please note that, when you want to look at the frequency, the reads need to be divided by the total frame reads.

4: Updated Gene Names (Comparison with The Name Used Before September 2017)

  • Application:
  • To correspond to the latest IMGT nomenclature and classification for IG and TR genes, our database has been updated and the information will be reflected in our analysis report from September 2017.
  • Please check whether the names of genes that you tested previously have been changed
  • If you encounter any problems, please let us know your species ID and gene name.
  • We are happy to help you to solve any problems.

To Researchers

FAQ