Pre-processed IgH receptor repertoire data from MS patients after aHSCT from BioProject PRJNA763367

<strong>Data Processing</strong> Samples were demultiplexed via their Illumina indices, and processed using the Immcantation toolkit(1,2). Raw fastq files were filtered based on a quality score threshold of 20. Paired reads were joined if they had a minimum length of 10 nt, maximum error rate of 0.3 and a significance threshold of 0.0001. Reads with identical UMI were collapsed to a consensus sequence. Reads with identical full-length sequence and identical constant primer but differing UMI were further collapsed. Sequences were then submitted to IgBlast (3) for VDJ assignment and sequence annotation. Constant region sequences were mapped to germline using Stampy(4). The number and type of V gene mutations was calculated using the shazam R package.(2) <strong>software_versions</strong> pRESTO:0.5.3,Change-O:0.3.4,IgBlast 1.6.1, stampy1.0.21. shazam0.1.8 <strong>quality_thresholds</strong> FilterSeq.py pRESTO Q&gt;20 <strong>paired_reads_assembly</strong> AssemblePairs.py pRESTO minlen 10 maxerror 0.3 alpha 0.0001 <strong>primer_match_cutoffs</strong> MaskPrimers.py pRESTO C primer &amp; V primer maxerror 0.2 <strong>consensus_building</strong> BuildConsensus.py pRESTO maxerror 0.1 maxgap 0.5 <strong>collapsing_method</strong> CollapseSeq.py pRESTO <strong>germline_database </strong>IMGT <strong>Format</strong> Processed sequences are provided in a tab delimited file format, including the following annotations: <strong>ISOTYPE_SUBCLASS </strong>Isotype subclass <strong>SEQUENCE_ID </strong>Sequence identifier <strong>JUNCTION_LENGTH </strong>Junction length <strong>CONSCOUNT </strong>Raw read count from which UMI consensus sequences were generated, summed over all UMIs for the given unique sequence. <strong>DUPCOUNT </strong>UMI count for the given unique sequence <strong>ISOTYPE </strong>Constant region primer (isotype) <strong>MUT_TOTAL </strong>Total number of mutations in V gene <strong>SAMPLE </strong>Sample identifier, linking back to raw data <strong>JUNCTION </strong>Junction nucleotide sequence <strong>Protein_seq </strong>Amino acid sequence <strong>CDR3_AA_GRAVY </strong>CDR3 hydrophobicity index <strong>CDR3_AA_BULK </strong>CDR3 bulkiness <strong>CDR3_AA_ALIPHATIC </strong>CDR3 aliphatic index <strong>CDR3_AA_POLARITY </strong>CDR3 polarity <strong>CDR3_AA_CHARGE </strong>CDR3 normalized net charge <strong>CDR3_AA_BASIC </strong>CDR3 basic side chain residue content <strong>CDR3_AA_ACIDIC </strong>CDR3 acidic side chain residue content <strong>CDR3_AA_AROMATIC </strong>CDR3 aromatic side chain content <strong>Subset </strong>Defined B cell subset <strong>Repertoire </strong>Defined B cell repertoire (Naive, Memory IgM/IgD, IgA, IgG) <strong>R_SCDR </strong>R/S ratio in CDR region <strong>R_SFWR </strong>R/S ratio in FWR region <strong>V_GENE </strong>V segment gene <strong>D_GENE </strong>D segment gene <strong>J_GENE </strong>J segment gene <strong>V_FAM </strong>V family gene <strong>Clust_REPRES </strong>Cluster representative <strong>Clust_SIZE </strong>Cluster size <strong>Sex </strong>Sex of the Subject <strong>UNIQUE_ID </strong>Sample identifier <strong>Bcellno </strong>Input B cell number <strong>Days_posttx </strong>Sampling time point relative to transplantation <strong>Age_at_tx </strong>Age of the subject (at aHSCT) <strong>Disease </strong>MS subtype <strong>Last_therapy </strong>Last therapy prior to aHSCT <strong>Disease_duration </strong>Disease duration <strong>CMV_reactivation </strong>Cytomegalovirus reactivation <strong>Month_label </strong>Month post-aHSCT inverval bin <strong>Patient_label </strong>Subject identifier <pre> </pre> <strong>References</strong> 1. Vander Heiden, J. A., G. Yaari, M. Uduman, J. N. H. Stern, K. C. O’Connor, D. A. Hafler, F. Vigneault, and S. H. Kleinstein. 2014. PRESTO: A toolkit for processing high-throughput sequencing raw reads of lymphocyte receptor repertoires. <em>Bioinformatics</em>30: 1930–1932. 2. Gupta, N. T., J. A. Vander Heiden, M. Uduman, D. Gadala-Maria, G. Yaari, and S. H. Kleinstein. 2015. Change-O: A toolkit for analyzing large-scale B cell immunoglobulin repertoire sequencing data. <em>Bioinformatics</em>31: 3356–3358. 3. Ye, J., N. Ma, T. L. Madden, and J. M. Ostell. 2013. IgBLAST: an immunoglobulin variable domain sequence analysis tool. <em>Nucleic Acids Res.</em>41. 4. Lunter, G., and M. Goodson. 2011. Stampy: A statistical algorithm for sensitive and fast mapping of Illumina sequence reads. <em>Genome Res.</em>21: 936–939.