pipeAIRR - Github repository for Adaptive immune receptor repertoire ViaFoundry pipelines

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Welcome

pipeAIRR is a community resource for adaptive immune receptore repertoire sequencing (AIRR-seq) processing pipelines.

The pipelines are implemented with ViaFoundry.

We have divided the pipelines into two main sections:

  1. Pre-processing
  2. Downstream analysis

Repository layout

For each pipeline you can find a directory containing the ViaFoundry pipeline (main.dn) as well as the configurations and the nextflow script (main.nf)

Pre-processing

In this section you can find pipelines to process the sequencer output files, meaning from ‘raw reads’ into an aligner ready fasta file.

In this section you can find pipelines to process the sequencer output files, from ‘raw reads’ into a fasta file ready to be used as an input for an alignment step and other downstream tasks.

The pipeplines were built based on the immcantation framework and specifically the pRESTO tool suite.

Available pipelines:

Pipeline Input data Sequencing protocol UMI Published paper(s) GitHub Archive Zenodo DOI ViaFoundry pipeline
RP1 Raw sequences 2X250 + [11] pipeAIRR/RP1 DOI pipeline/381
RP2 Raw sequences 2X250 - [4] pipeAIRR/RP2 DOI pipeline/382
RP3 Raw sequences 5’ RACE + [3], [1] pipeAIRR/RP3 DOI pipeline/383
RP4 Raw sequences 2X300 + [2] pipeAIRR/RP4 DOI pipeline/386
RP5 Raw sequences 5’ RACE + [9] pipeAIRR/RP5A, pipeAIRR/RP5B DOI, DOI pipeline/390, pipeline/393
RP6 Raw sequences Roche 454 - [5] pipeAIRR/RP6 DOI pipeline/396
RP7 Raw sequences 2X125 CD4 - [8] pipeAIRR/RP7 DOI
pipeline/397

Downstream analysis

In this section you can find pipelines to analyze processed reads and infer genotype and haplotype. The pipelines were built based on the Yaari lab framework, which contains tools from: - immcantaton - VDJbase - TIgGER - RAbHIT - PIgLET

Available pipelines:

Pipeline Input data Sequencing protocol UMI Published paper(s) GitHub Archive Zenodo DOI ViaFoundry pipeline
PP1 Processed sequences - - [10] pipeAIRR/PP1 DOI pipeline/401
PP2 Processed sequences - - [6] pipeAIRR/PP2 DOI pipeline/402
PP3 Processed sequences - - [7] pipeAIRR/PP3 DOI pipeline/398
  • Processed sequences are the fasta file from the pre-processing step.

ViaFoundry access

Please note to access the ViaFoundry pipeline you will need to create an account. You can create an account by contacting the ViaFoundry team support@viascientific.com, for further information please go here

Citations:

[1] Sivan Eliyahu, Oz Sharabi, Shiri Elmedvi, Reut Timor, Ateret Davidovich, Francois Vigneault, Chris Clouser, Ronen Hope, Assy Nimer, Marius Braun, Yaacov Y. Weiss, Pazit Polak, Gur Yaari, and Meital Gal-Tanamy. Antibody repertoire analysis of hepatitis c virus infections identifies immune signatures associated with spontaneous clearance. Frontiers in Immunology, 9:3004, 2018

[2] Jacob D Galson, Sebastian Schaetzle, Rachael JM Bashford-Rogers, Matthew IJ Ray-313 bould, Aleksandr Kovaltsuk, Gavin J Kilpatrick, Ralph Minter, Donna K Finch, Jorge314 Dias, Louisa K James, et al. Deep sequencing of b cell receptor repertoires from covid-315 19 patients reveals strong convergent immune signatures. Frontiers in immunology,316 11:605170, 2020.

[3] Moriah Gidoni, Omri Snir, Ayelet Peres, Pazit Polak, Ida Lindeman, Ivana Mikocziova, Vikas Kumar Sarna, Knut EA Lundin, Christopher Clouser, Francois Vigneault, et al. Mosaic deletion patterns of the human antibody heavy chain gene locus shown by bayesian haplotyping. Nature communications, 10(1):1–14, 2019

[4] Victor Greiff, Ulrike Menzel, Ulrike Haessler, Skylar C Cook, Simon Friedensohn, Tarik A Khan, Mark Pogson, Ina Hellmann, and Sai T Reddy. Quantitative assessment of the robustness of next-generation sequencing of antibody variable gene repertoires from immunized mice. BMC immunology, 15:1–14, 2014.

[5] Ning Jiang, Jiankui He, Joshua A Weinstein, Lolita Penland, Sanae Sasaki, Xiao-Song He, Cornelia L Dekker, Nai-Ying Zheng, Min Huang, Meghan Sullivan, et al. Lineage structure of the human antibody repertoire in response to influenza vaccination. Science translational medicine, 5(171):171ra19–171ra19, 2013

[6] Aviv Omer, Or Shemesh, Ayelet Peres, Pazit Polak, Adrian J Shepherd, Corey T Watson, Scott D Boyd, Andrew M Collins, William Lees, and Gur Yaari. Vdjbase: an adaptive immune receptor genotype and haplotype database. Nucleic acids research, 48(D1):D1051–D1056, 2020

[7] Ayelet Peres, William D Lees, Oscar L Rodriguez, Noah Y Lee, Pazit Polak, Ronen Hope, Meirav Kedmi, Andrew M Collins, Mats Ohlin, Steven H Kleinstein, Corey T Watson, and Gur Yaari. IGHV allele similarity clustering improves genotype inference from adaptive immune receptor repertoire sequencing data. Nucleic Acids Research, page gkad603, 08 2023.

[8] Teresa Rubio, Maria Chernigovskaya, Susanna Marquez, Cristina Marti, Paula Izquierdo-Altarejos, Amparo Urios, Carmina Montoliu, Vicente Felipo, Ana Conesa, Victor Greiff, et al. A nextflow pipeline for t-cell receptor repertoire reconstruction and analysis from rna sequencing data. ImmunoInformatics, 6:100012, 2022.

[9] Modi Safra, Zvi Tamari, Pazit Polak, Shachaf Shiber, Moshe Matan, Hani Karameh, Yigal Helviz, Adva Levy-Barda, Vered Yahalom, Avi Peretz, et al. Altered somatic hypermutation patterns in covid-19 patients classifies disease severity. Frontiers in Immunology, 14:1031914, 2023.13

[10] Modi Safra, Lael Werner, Ayelet Peres, Pazit Polak, Naomi Salamon, Michael Schvimer, Batia Weiss, Iris Barshack, Dror S Shouval, and Gur Yaari. A somatic hypermutation based machine learning model stratifies individuals with crohn’s disease and controls. Genome Research, 33(1):71–79, 2023

[11] Joel NH Stern, Gur Yaari, Jason A Vander Heiden, George Church, William F Donahue, Rogier Q Hintzen, Anita J Huttner, Jon D Laman, Rashed M Nagra, Alyssa Nylander, et al. B cells populating the multiple sclerosis brain mature in the draining cervical lymph nodes. Science translational medicine, 6(248):248ra107–248ra107, 2014