Advanced topics

IgDiscover itself does not (yet) come with all imaginable analysis facilities built into it. However, it creates many files (mostly with tables) that can be used for custom analysis. For example, all .tab files (in particular and can be opened and inspected in a spreadsheet application such as LibreOffice. From there, you can do basic tasks such as sorting from the menu of that application.

Often, these facilities are not enough, however, and some basic understanding of the command-line is helpful. Clearly, this is not as convenient as working in a graphical user interface (GUI), but we do not currently have the resources to provide one for IgDiscover. To alleviate this somewhat, we provide here instructions for a few things that you may want to do with the IgDiscover result files.

Extract all sequences that match any database gene exactly

The file tells you for each discovered sequence how often an exact match of that sequence was found in your input reads. A high number of exact matches is a good indication that the candidate is actually a new gene or allele. In order to find the original reads that correspond to those matches, you can look at the file and extract all rows where the V_errors column is zero.

First, run this on the file:

zcat | head -n 1 | tr '\t' '\n' | nl

This will enumerate the columns in the file. Take a note of the index that the V_errors column has. In newer pipeline versions, the index is 21. Then extract all rows of the file where that field is equal to zero:

zcat | awk -vFS=”t” ‘$21 == 0 || NR == 1’ >

If the column wasn’t 21, then replace the $21 appropriately. The part where it says NR == 1 ensures that the column headings are also printed.

Extra configuration settings

Some configuration settings are not documented in the default igdiscover.yaml file since they rarely need to be changed.

# Leave empty or choose a species name supported by IgBLAST:
# human, mouse, rabbit, rat, rhesus_monkey
# This setting is not used anywhere except that it is passed
# to IgBLAST using the -organism option. Since we provide IgBLAST
# with our own gene databases, it seems this has no effect.
# Which program to use for computing multiple alignments. This is used for
# computing consens sequences.
# Choose 'mafft', 'clustalo', 'muscle' or 'muscle-fast'.
# 'muscle-fast' runs muscle with parameters "-maxiters 1 -diags".
#multialign_program: muscle-fast