Clonal clustering methods

The DefineClones tool provides multiple different approaches to assigning Ig sequences into clonal groups.

Clustering by V-gene, J-gene and junction length

All methods provided by DefineClones first partition sequences based on common IGHV gene, IGHJ gene, and junction region length. These groups are then further subdivided into clonally related groups based on the following distance metrics on the junction region. The specified distance metric (--model) is then used to perform hierarchical clustering under the specified linkage (--link) clustering. Clonal groups are defined by trimming the resulting dendrogram at the specified threshold (--dist).

Amino acid model

The aa distance model is the Hamming distance between junction amino acid sequences.

Hamming distance model

The ham distance model is the Hamming distance between junction nucleotide sequences.

Human and mouse 1-mer models

The hh_s1f and mk_rs5nf distance models are single nucleotide distance matrices derived from averaging and symmetrizing the human 5-mer targeting model in [YVanderHeidenU+13] and the mouse 5-mer targeting model in [CDiNiroVanderHeiden+16]. The are broadly similar to a transition/transversion model.

Human 1-mer substitution matrix:

Nucleotide

A

C

G

T

N

A

0

1.21

0.64

1.16

0

C

1.21

0

1.16

0.64

0

G

0.64

1.16

0

1.21

0

T

1.16

0.64

1.21

0

0

N

0

0

0

0

0

Mouse 1-mer substitution matrix:

Nucleotide

A

C

G

T

N

A

0

1.51

0.32

1.17

0

C

1.51

0

1.17

0.32

0

G

0.32

1.17

0

1.51

0

T

1.17

0.32

1.51

0

0

N

0

0

0

0

0

Human and mouse 5-mer models

The hh_s5f and mk_rs5nf distance models are based on the human 5-mer targeting model in [YVanderHeidenU+13] and mouse 5-mer argeting models in [CDiNiroVanderHeiden+16], respectively. The targeting matrix T has 5-mers across the columns and the nucleotide to which the center base of the 5-mer mutates as the rows. The value for a given nucleotide, 5-mer pair T[i,j] is the product of the likelihood of that 5-mer to be mutated mut(j) and the likelihood of the center base mutating to the given nucleotide sub(j\rightarrow i). This matrix of probabilities is converted into a distance matrix D via the following steps:

  1. D = -log10(T)

  2. D is then divided by the mean of values in D

  3. All distances in D that are infinite (probability of zero), distances on the diagonal (no change), and NA distances are set to 0.

Since the distance matrix D is not symmetric, the --sym argument can be specified to calculate either the average (avg) or minimum (min) of D(j\rightarrow i) and D(i\rightarrow j). The distances defined by D for each nucleotide difference are summed for all 5-mers in the junction to yield the distance between the two junction sequences.

CDiNiroVanderHeiden+16(1,2)

Ang Cui, Roberto Di Niro, Jason A. Vander Heiden, Adrian W. Briggs, Kris Adams, Tamara Gilbert, Kevin C. O’Connor, Francois Vigneault, Mark J. Shlomchik, and Steven H. Kleinstein. A Model of Somatic Hypermutation Targeting in Mice Based on High-Throughput Ig Sequencing Data. The Journal of Immunology, 197(9):3566–3574, nov 2016. URL: http://www.jimmunol.org/content/197/9/3566.abstract http://www.jimmunol.org/lookup/doi/10.4049/jimmunol.1502263, doi:10.4049/jimmunol.1502263.

YVanderHeidenU+13(1,2)

Gur Yaari, Jason A Vander Heiden, Mohamed Uduman, Daniel Gadala-Maria, Namita Gupta, Joel N H Stern, Kevin C O’Connor, David A Hafler, Uri Laserson, Francois Vigneault, and Steven H Kleinstein. Models of somatic hypermutation targeting and substitution based on synonymous mutations from high-throughput immunoglobulin sequencing data. Frontiers in immunology, 4:358, January 2013. URL: http://www.pubmedcentral.nih.gov/articlerender.fcgi?artid=3828525\&tool=pmcentrez\&rendertype=abstract, doi:10.3389/fimmu.2013.00358.