Quality control pipeline for antibody libraries
Table of contents
- abseqPy Installation
- Supported platforms
AbSeq is a comprehensive bioinformatic pipeline for the analysis of sequencing datasets generated from antibody libraries and
abseqPy is one of its packages. Given FASTQ or FASTA files (paired or single-ended),
generates clonotypes tables, V-(D)-J germline annotations, functional rates, and
diversity estimates in a combination of csv and HDF files. More specialized analyses for antibody libraries
like primer specificity, sequence motif analysis, and restriction sites analysis are also on the list.
This program is intended to be used in conjunction with
a reporting and statistical analysis package for the data generated by
abseqPy works fine without
abseqR, it is highly recommended that users also install the R package in order to take the advantage of the interactive HTML reporting capabilities of the pipeline.
abseqR's project page shows a few examples of the type of analysis
AbSeq provides; the full documentation can be found in
AbSeqis developed by Monther Alhamdoosh and JiaHong Fong
- For comments and suggestions, email m.hamdoosh <at> gmail <dot> com
abseqPy depends on a few external software to work and they should be properly
installed and configured before running
abseqPyruns on Python 2.7. Python 3.6 support is underway.
Seamless installation of dependencies
This is the recommended way of installing abseqPy's external dependencies.
A python script is available here which downloads and installs all the necessary external dependencies.
This script assumes the following is already available:
- Java JRE version 1.6 or higher
- C/C++ compilers (not required for Windows)
- make (not required for Windows)
- CMake (not required for Windows)
To install external dependencies into a folder named
$ mkdir -p ~/.local/abseq $ python install_dependencies.py ~/.local/abseq
This script does not install
abseqPyitself, only its external dependencies.
This script works with Python 2 and 3, and
~/.local/abseq can be replaced with any directory.
- this directory will be there to stay, so choose wisely
- the installation script will dump more than just binaries in this directory, it will contain databases and internal files
as soon as the installation succeeds, users will be prompted with an onscreen message
to update their environment variables to include installed dependencies in
Manual installation of dependencies
This section is for when one:
- finds that the installation script failed
- is feeling adventurous
refer to this document for a detailed guide.
This section demonstrates how to install
$ pip install abseqPy
Install from source
$ git clone https://github.com/malhamdoosh/abseqPy.git $ cd abseqPy $ pip install . $ abseq --version
abseq command should now be available on your command line.
To get up and running, the following command is often sufficient:
$ abseq -f1 <read 1> -f2 <read 2> -o results --threads 4 --task all
-f2 is only required if it is a paired-end sequencing experiment.
abseq with command line options,
abseq also supports
-y <file> or
that reads parameters defined in
file. This enables multiple samples to be analyzed at the same time, each
having shared or independent
The basic YAML syntax of
key: val where
key is an
"long"1 option (see
abseq --help for all the "long" option names) and
val is the value supplied to the "long" option. Additional samples are specified one after another
separated by triple dashes
Assuming a file named
example.yml has the following content:
# sample one, PCR1 name: PCR1 file1: fastq/PCR1_R1.fastq.gz file2: fastq/PCR1_R2.fastq.gz --- # sample two, PCR2 name: PCR2 file1: fastq/PCR2_R1.fastq.gz file2: fastq/PCR2_R2.fastq.gz bitscore: 300 # override the defaults' 350 for this sample only task: abundance # override the defaults' "all" for this sample only detailedComposition: ~ # enables detailedComposition (-dc) for this sample only --- # more samples can go here --- # "defaults" is the only special key allowed. # It is not in abseq's options, but is used here # to denote default values to be used for ALL samples # if they're not specified. defaults: task: all outdir: results threads: 7 bitscore: 350 sstart: 1-3
abseq -y example.yml is equivalent to simultaneously running 2 instances of
abseq with the parameters in the
defaults field applied to both samples. Here's an
$ abseq --task all --outdir results --threads 7 --bitscore 350 --sstart 1-3 \ > --name PCR1 --file1 fastq/PCR1_R1.fastq.gz --file2 fastq/PCR1_R2.fastq.gz $ abseq --task abundance --outdir results --threads 7 --bitscore 300 --sstart 1-3 \ > --name PCR2 --file1 fastq/PCR2_R1.fastq.gz --file2 fastq/PCR2_R2.fastq.gz \ > --detailedComposition
--yaml is recommended because it is self-documenting, reproducible, and simple to run.
- In the above example, specifying
threads: 7in the
example.ymlwill run each sample with 7 threads, that is,
abseqPywill be running with 7 *
number of samplestotal processes.
abseq -h in the command line will display the options
abseqPy works on most Linux distros, macOS, and Windows.
Some features are disabled when running in Windows due to software incompatibility, they are:
- Upstream clustering in
- Sequence logo generation in
<small>1</small><small> long option names are option names with a double dash prefix, for example,
--help is a long option while
-h is not ↩</small>
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