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Table 1 Tool categories, a brief description of their roles and a list of exemplar tools

From: Best practices for bioinformatic characterization of neoantigens for clinical utility

Tool categories Function and examples
Alignment DNA: Bwa-mem [161] RNA: STAR [162], HISAT2 [163]
Sequence data QC Picard (http://broadinstitute.github.io/picard/), FastQC (https://github.com/s-andrews/FastQC), RSeQC [164], MultiQC (https://github.com/ewels/MultiQC) (note that MultiQC supports an extensive list of additional QC tools)
Variant callers SNV/Indel: Mutect [19], Strelka [20], VarScan2 [21], SomaticSniper [22], Shimmer [165], VarDict [166], deepSNV [167], EBCall [40] Structural variants: Pindel [43], Manta [168], Lumpy [169] Fusions: STAR-Fusion [48], Pizzly [47], SOAPfuse [170], JAFFA [49], ChimPipe [171], GFusion [50], INTEGRATE [51]
Variant call format (VCF) manipulation Vt decompose (https://github.com/atks/vt), GATK (https://github.com/broadinstitute/gatk) (e.g., SelectVariants, CombineVariants, LeftAlignAndTrimVariants)
Variant annotation Variant Effect Predictor (VEP) (https://github.com/Ensembl/ensembl-vep) (SNV/Indel), AGFusion [172] (RNA fusions), bam-readcount (https://github.com/genome/bam-readcount), VAtools (https://github.com/griffithlab/VAtools)
Gene or transcript abundance estimation StringTie [173], Kallisto [174]
HLA typing Class I: Optitype [69], Polysolver [70] Class I and II: Athlates [70, 175], HLAreporter [176], HLAminer [176, 177], HLAscan [72, 178], HLA-VBSeq [72], PHLAT [71], seq2HLA [73], xHLA [74]
Peptide processing Proteasome cleavage: NetChop20S [89], NetChopCterm [89], ProteaSMM [89, 90], PAProC [179] (Class I), PepCleaveCD4 [91] (Class II) TAP transport efficiency: [90] (no specific tool name)
MHC binding predictors Class I predictors: SMM [111], SMMPMBEC [112], Pickpocket [113], NetMHC [114], NetMHCpan [87], NetMHCcons [180], MHCflurry [102], MHCnuggets [181], MHCSeqNet [103], EDGE [104] Class II predictors: SMMAlign [111], NNAlign [182], ProPred [183], NetMHCII(2.3) and NetMHCIIpan(3.2) [116], TEPITOPE [184], TEPITOPEpan [185], RANKPEP [186], MultiRTA [187], OWA-PSSM [188]
Neoantigen prioritization pipelines pVACtools [8], Vaxrank [9], MuPeXI [119], TIminer [120], Neoepiscope [189], TSNAD [190], EpiToolKit [123], NeoepitopePred [122], TepiTool (IEDB) [191], ScanNeo [192], CloudNeo [193], NeoPredPipe [118]
Peptide creation and delivery pVACtools [8] (pVACvector), Vaxrank [9] (manufacturability)
TCR repertoire profiling LymAnalyzer [194], MiXCR [147], MIGEC [148], pRESTO [195], TRUST [196], TraCeR [145], VDJtools [197], VDJviz [198], ImmunoSEQ [199], GLIPH [151]
Immune cell profiling CIBERSORT [152], TIMER [153], quanTIseq [200], immunophenogram [201], MCPcounter [202], SSGSEA [203]
  1. This table compiles the current state of tools, databases, and other resources that are used in neoantigen pipelines. Although many of the steps that are outlined may involve the integration of multiple tools for comparable predictions (e.g., using multiple somatic variant callers or MHC-binding-affinity predictors), this table summarizes more options than are needed in a single workflow. For an example of the specific combination of tools, parameter settings, and order of operations used in a real end-to-end workflow that is based on our own practices, please refer to our online tutorial for precision medicine bioinformatics (https://pmbio.org/). TAP Transporter associated with antigen processing