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Fig. 1 | BMC Medical Genomics

Fig. 1

From: neoANT-HILL: an integrated tool for identification of potential neoantigens

Fig. 1

Overall workflow of neoANT-HILL. The neoANT-HILL was designed to analyze NGS data, such as genome (WGS or WES) and transcriptome (RNA-Seq) data. Basically, it takes as input distinct data types, including raw and pre-aligned sequences from RNA-Seq, as well as, variant calling files (VCF) from genome or transcriptome data (dotted lines indicate that the VCF must be previously created by the user). The blue boxes represent the transcriptome analyses, which should be carried out using data in either BAM format (variant calling) or fastq format (expression, HLA typing and tumor-infiltrating immune cells). The neoANT-HILL can perform gene expression (Kallisto), variant calling (GATK4 | Mutect2), HLA typing (Optitype), and Tumor-infiltrating immune cells (quanTIseq). The gene expression quantification is used as input to identify molecular signatures associated with immune cell diversity into the tumor samples. On the other hand, the gray boxes represent common steps to genome and transcriptome data. NeoANT-HILL uses the variant calling data to reconstruct the proteins sequences using as reference the NCBI RefSeq database. The VCF files can be either generated by using our pipeline or by external somatic variant-calling software. Next, reconstructed proteins are submitted to neoepitope binding prediction using HLA alleles from Optitype results or defined by the user. Finally, all steps and results are shown into a user-friendly interface

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