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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