NAb-seq (nextflow version)

NAb-seq is an accurate, rapid and cost-effective method for antibody long-read sequencing in hybridoma cell lines and single B cells.

Useful links

• The NAb-seq manuscript
• The NAb-seq documentation website
• The original version of NAb-seq
• The data from the NAb-seq manuscript

Usage

Also see the documentation for more usage information

Usage: nextflow run ./nabseq_nf/main.nf --fastq_dir [input path] --organism [organism name] --sample_sheet [sample sheet]
--help                : prints this help message

Required arguments:
--out_dir             : where the output files will be written to (default: "$projectDir/results)
--fastq_dir           : where the input fastq files are located
--sample_sheet        : location of the .csv sample sheet (format: barcode01,sample_x,rat,1)

Optional (only needed for advanced users)
--num_consensus       : maximum number of consensus sequences to generate for each sample (default: 999)
--igblast_databases   : location of the igblast databases (default: "$projectDir/references/igblast/")
--reference_sequences : location of the reference sequences (default: "$projectDir/references/reference_sequences/")
--trim_3p             : pattern for cutadapt to trim off the 3' end (default: "A{20}N{90}")
--trim_5p             : pattern for cutadapt to trim off the 5' end (default: "")
--medaka_model        : model to use for medaka (depends on your basecalling model, default:"r941_min_sup_g507")
--report_title        : title to use for naming the report (default: "NAb-seq report")

Input

NAb-seq requires as input:

• The path of a directory where it should write the results
• The path of the directory containing the basecalled and demultiplexed nanopore reads. NAb-seq expects either:
  • (default) A directory containing all fastqs, starting with barcode names (e.g. barcode01_pass.fq.gz)
  • (using --barcode_dirs TRUE) A directory containing a folder for each barcode name, which can contain as many different fastqs as you like
  • For more detailed information, see the tutorial website
• The name of the organism whose reference sequences should be used (rat and mouse are built-in, and you can create custom references for any organism you like
• A sample sheet (CSV) in the format: barcode,sample_name,species,report_group
  • Note that species should match exactly (case sensitive!) the names of files/folders in the references folder. Rat (Rattus norvegicus) and mouse (Mus musculus) references are built-in (referred to as rat and mouse respectively). You can create custom references for any organism you like.
  • The report_group column is used to control which samples are reported together. If you want all samples in a single report, just use 1 for each row.
  • For more detailed information about sample sheets, check out the tutorial website! There are also example sample sheets there that you can download and edit

Output

NABseq will produce a report containing sample/run information, QC metrics and the annotation results of productive sequences from all samples. All consensus sequences in FASTA format, as well as intermediate files (NanoComp QC results, IgBLAST results) are written to the results directory also