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

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Data Processing 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)   software_versions            pRESTO:0.5.3,Change-O:0.3.4,IgBlast 1.6.1, stampy1.0.21. shazam0.1.8 quality_thresholds            FilterSeq.py pRESTO Q>20 paired_reads_assembly        AssemblePairs.py pRESTO minlen 10 maxerror 0.3 alpha 0.0001 primer_match_cutoffs        MaskPrimers.py pRESTO C primer & V primer maxerror 0.2 consensus_building        BuildConsensus.py pRESTO maxerror 0.1 maxgap 0.5 collapsing_method        CollapseSeq.py pRESTO germline_database        IMGT   Format Processed sequences are provided in a tab delimited file format, including the following annotations:   ISOTYPE_SUBCLASS                    Isotype subclass SEQUENCE_ID                Sequence identifier JUNCTION_LENGTH            Junction length CONSCOUNT                Raw read count from which UMI consensus sequences were generated, summed over all UMIs for the given unique sequence. DUPCOUNT                    UMI count for the given unique sequence ISOTYPE                    Constant region primer (isotype) MUT_TOTAL                    Total number of mutations in V gene  SAMPLE                    Sample identifier, linking back to raw data JUNCTION                    Junction nucleotide sequence Protein_seq                    Amino acid sequence CDR3_AA_GRAVY                CDR3 hydrophobicity index CDR3_AA_BULK                CDR3 bulkiness CDR3_AA_ALIPHATIC                CDR3 aliphatic index CDR3_AA_POLARITY                CDR3 polarity CDR3_AA_CHARGE                CDR3 normalized net charge CDR3_AA_BASIC                CDR3 basic side chain residue content CDR3_AA_ACIDIC            CDR3 acidic side chain residue content CDR3_AA_AROMATIC                CDR3 aromatic side chain content Subset                    Defined B cell subset  Repertoire                    Defined B cell repertoire (Naive, Memory IgM/IgD, IgA, IgG) R_SCDR                    R/S ratio in CDR region R_SFWR                    R/S ratio in FWR region V_GENE                    V segment gene D_GENE                    D segment gene J_GENE                    J segment gene V_FAM                    V family gene Clust_REPRES                Cluster representative Clust_SIZE                    Cluster size Sex                        Sex of the Subject UNIQUE_ID                    Sample identifier  Bcellno                    Input B cell number Days_posttx                        Sampling time point relative to transplantation Age_at_tx                        Age of the subject (at aHSCT) Disease                        MS subtype Last_therapy                        Last therapy prior to aHSCT Disease_duration                        Disease duration CMV_reactivation                        Cytomegalovirus reactivation Month_label                        Month post-aHSCT inverval bin Patient_label                        Subject identifier   References 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. Bioinformatics30: 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. Bioinformatics31: 3356–3358. 3. Ye, J., N. Ma, T. L. Madden, and J. M. Ostell. 2013. IgBLAST: an immunoglobulin variable domain sequence analysis tool. Nucleic Acids Res.41. 4. Lunter, G., and M. Goodson. 2011. Stampy: A statistical algorithm for sensitive and fast mapping of Illumina sequence reads. Genome Res.21: 936–939.
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2021-10-01
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