ylab-hi/ScanNeo2

Snakemake-based computational workflow for neoantigen prediction from diverse sources

Overview

Latest release: v0.3.14, Last update: 2026-05-25

Share link: https://snakemake.github.io/snakemake-workflow-catalog?wf=ylab-hi/ScanNeo2

Quality control: linting: passed formatting: failed

Topics: epitope gene-fusion indels neoantigens peptide snakemake snakemake-workflow splicing exitron neoepitope immunotherapy vaccine

Wrappers: bio/arriba bio/bcftools/concat bio/bcftools/index bio/bowtie2/align bio/bowtie2/build bio/bwa/index bio/fastp bio/fastqc bio/gatk/applybqsr bio/gatk/applyvqsr bio/gatk/baserecalibrator bio/gatk/filtermutectcalls bio/gatk/haplotypecaller bio/gatk/mutect bio/gatk/selectvariants bio/gatk/variantrecalibrator bio/picard/createsequencedictionary bio/samtools/faidx bio/samtools/index bio/samtools/merge bio/star/align bio/star/index bio/tabix/index bio/vep/annotate

Deployment

Step 1: Install Snakemake and Snakedeploy

Snakemake and Snakedeploy are best installed via the Conda package manager. It is recommended to install conda via Miniforge. Run

conda create -c conda-forge -c bioconda -c nodefaults --name snakemake snakemake snakedeploy

to install both Snakemake and Snakedeploy in an isolated environment. For all following commands ensure that this environment is activated via

conda activate snakemake

For other installation methods, refer to the Snakemake and Snakedeploy documentation.

Step 2: Deploy workflow

With Snakemake and Snakedeploy installed, the workflow can be deployed as follows. First, create an appropriate project working directory on your system and enter it:

mkdir -p path/to/project-workdir
cd path/to/project-workdir

In all following steps, we will assume that you are inside of that directory. Then run

snakedeploy deploy-workflow https://github.com/ylab-hi/ScanNeo2 . --tag v0.3.14

Snakedeploy will create two folders, workflow and config. The former contains the deployment of the chosen workflow as a Snakemake module, the latter contains configuration files which will be modified in the next step in order to configure the workflow to your needs.

Step 3: Configure workflow

To configure the workflow, adapt config/config.yml to your needs following the instructions below.

Step 4: Run workflow

The deployment method is controlled using the --software-deployment-method (short --sdm) argument.

To run the workflow with automatic deployment of all required software via conda/mamba, use

snakemake --cores all --sdm conda

Snakemake will automatically detect the main Snakefile in the workflow subfolder and execute the workflow module that has been defined by the deployment in step 2.

For further options such as cluster and cloud execution, see the docs.

Step 5: Generate report

After finalizing your data analysis, you can automatically generate an interactive visual HTML report for inspection of results together with parameters and code inside of the browser using

snakemake --report report.zip

Configuration

The following section is imported from the workflow’s config/README.md.

Configuring ScanNeo2

ScanNeo2 is configured through a single YAML file, config/config.yaml. The default file ships with sensible values for every section; you typically only need to edit the data: section to point at your inputs.

Run the workflow with the default configuration:

snakemake --cores all --software-deployment-method conda

…or with a custom configuration file at any path:

snakemake --cores all --software-deployment-method conda \
          --configfile /path/to/my-config.yaml

Paths in the config file are resolved relative to the directory from which you invoke snakemake.

The sections below mirror the structure of config/config.yaml. The schema is defined in workflow/schemas/config.schema.yaml; its parameter table is rendered automatically by the Snakemake Workflow Catalog.

reference — reference genome & annotation

Key

Type

Default

Description

reference.release

int

111

Ensembl release used to download the reference genome and annotation.

reference.nonchr

bool

false

Include non-chromosomal / scaffold contigs in the reference.

threads, mapq, basequal — global limits

Key

Type

Default

Description

threads

int

30

Upper bound on threads any single rule may use. Effective threads per rule are min(rule.threads, --cores).

mapq

int

30

Minimum read mapping quality (MAPQ, Phred-scaled) used during filtering.

basequal

int

20

Minimum base-call quality (Phred-scaled) used during filtering.

data — input samples

The data section is the only block that must be edited.

Key

Type

Description

data.name

str

Run name. Results are written to results/<name>/.

data.dnaseq

mapping

DNA-seq inputs, one entry per group. Key = group name; value = one path (single-end) or two space-separated paths (paired-end). Accepted extensions: .fastq / .fq / .bam.

data.rnaseq

mapping

RNA-seq inputs, same format as data.dnaseq.

data.normal

str

Group name of the matched normal/control sample (used for somatic calling). Leave empty if no matched normal exists.

data.custom.variants

path

Optional path to a user-supplied VCF to prioritize directly (bypassing variant calling).

data.custom.hlatyping.MHC-I

path

Optional path to a file listing MHC class I alleles (used when hlatyping.MHC-I_mode: custom).

data.custom.hlatyping.MHC-II

path

Optional path to a file listing MHC class II alleles (used when hlatyping.MHC-II_mode: custom).

Example data: block:

data:
  name: my_run
  dnaseq:
    tumor:  /path/to/dna_tumor_R1.fq.gz /path/to/dna_tumor_R2.fq.gz
    normal: /path/to/dna_normal.bam
  rnaseq:
    tumor:  /path/to/rna_tumor_R1.fq.gz /path/to/rna_tumor_R2.fq.gz
  normal: normal

preproc — fastq pre-processing

Applied only to FASTQ inputs (BAM inputs are not re-trimmed).

Key

Type

Default

Description

preproc.activate

bool

true

Whether to run pre-processing.

preproc.minlen

int

10

Discard reads shorter than this (bp) after trimming.

preproc.slidingwindow.activate

bool

true

Enable sliding-window quality trimming.

preproc.slidingwindow.wsize

int

3

Sliding-window size (bp).

preproc.slidingwindow.wqual

int

20

Mean base quality required within the window (Phred-scaled).

align — STAR chimeric alignment

Parameters passed to STAR for RNA-seq gene-fusion detection.

Key

Type

Default

Description

align.chimSegmentMin

int

20

Minimum length of each chimeric segment (0 disables chimeric detection).

align.chimScoreMin

int

10

Minimum total chimeric-alignment score.

align.chimJunctionOverhangMin

int

10

Minimum overhang length for a chimeric junction.

align.chimScoreDropMax

int

30

Maximum allowed drop of chimeric score below read length.

align.chimScoreSeparation

int

10

Minimum score separation between best and next-best chimeric alignment.

altsplicing — alternative splicing events

Key

Type

Default

Description

altsplicing.activate

bool

true

Include alternative-splicing events.

altsplicing.confidence

int

3

Confidence level (1–3) for filtering input alignments.

altsplicing.iterations

int

5

Number of intron-edge addition iterations (sensitivity vs runtime).

altsplicing.edgelimit

int

250

Maximum edges in the splice graph.

exitronsplicing — exitron splicing events

Key

Type

Default

Description

exitronsplicing.activate

bool

true

Include exitron-splicing events.

exitronsplicing.ao

int

3

Allele observation count.

exitronsplicing.pso

float

0.05

Percent spliced-out.

exitronsplicing.strand

int

1

Library strand specificity (0=unstranded, 1=forward, 2=reverse).

genefusion — Arriba gene-fusion calling

Key

Type

Default

Description

genefusion.activate

bool

true

Include gene-fusion events.

genefusion.maxevalue

float

0.3

Maximum E-value.

genefusion.suppreads

int

2

Minimum supporting reads (fusions below this are discarded).

genefusion.maxsuppreads

int

1000

Maximum supporting reads.

genefusion.maxidentity

float

0.3

Genes with identity above this fraction are treated as homologs and discarded.

genefusion.hpolymerlen

int

6

Remove breakpoints adjacent to homopolymers of this length.

genefusion.readthroughdist

int

10000

Distance (bp) below which adjacent breakpoints are considered read-through.

genefusion.minanchorlen

int

20

Discard fusions whose segments are shorter than this.

genefusion.splicedevents

int

4

Fusions between genes require at least this many spliced breakpoints.

genefusion.maxkmer

float

0.6

Remove reads where a repetitive 3-mer makes up more than this fraction.

genefusion.fraglen

int

200

Mean fragment length.

genefusion.maxmismatch

float

0.01

Maximum mismatch fraction.

indel — small variant calling

Key

Type

Default

Description

indel.activate

bool

true

Include indels & SNVs.

indel.type

str

all

long, short, or all.

indel.mode

str

BOTH

Call from DNA, RNA, or BOTH.

indel.strategy

str

OPTIMAL_F_SCORE

Posterior-probability threshold strategy: OPTIMAL_F_SCORE, FALSE_DISCOVERY_RATE, or CONSTANT.

indel.fscorebeta

float

1.0

Relative weight of recall to precision (used with OPTIMAL_F_SCORE).

indel.fdr

float

0.05

False-discovery rate target (used with FALSE_DISCOVERY_RATE).

indel.sliplen

int

8

Minimum reference bases to suspect a slippage event.

indel.sliprate

float

0.1

Suspected slippage frequency.

quantification — expression quantification

Key

Type

Default

Description

quantification.mode

str

BOTH

Quantify from DNA, RNA, or BOTH.

hlatyping — HLA typing

Key

Type

Default

Description

hlatyping.class

str

BOTH

HLA class to type: I, II, or BOTH.

hlatyping.MHC-I_mode

str

DNA, RNA

Source(s) for MHC-I typing: DNA, RNA, or custom (use data.custom.hlatyping.MHC-I).

hlatyping.MHC-II_mode

str

DNA, RNA

Source(s) for MHC-II typing.

hlatyping.freqdata

path

./hlahd_files/freq_data/

HLA-HD frequency-data directory (only required when class II is enabled).

hlatyping.split

path

./hlahd_files/HLA_gene.split.txt

HLA-HD gene-split file.

hlatyping.dict

path

./hlahd_files/dictionary/

HLA-HD dictionary directory.

HLA-HD must be installed and on PATH if class II is enabled — see the top-level README for installation notes.

prioritization — epitope prediction

Key

Type

Default

Description

prioritization.class

str

I

Epitope MHC class to predict: I, II, or BOTH.

prioritization.lengths.MHC-I

str

8,9,10,11

Comma-separated MHC-I epitope lengths (aa).

prioritization.lengths.MHC-II

str

13,14,15

Comma-separated MHC-II epitope lengths (aa).

For tutorials and worked examples, see the ScanNeo2 wiki.

Workflow parameters

The following table is automatically parsed from the workflow’s config.schema.y(a)ml file.

Parameter

Type

Description

Required

Default

reference

yes

. release

integer

Ensembl release used to download the reference genome and annotation

yes

. nonchr

boolean

whether to include non-chromosomal/scaffold contigs

yes

threads

integer

maximum number of threads any single rule may use

yes

mapq

integer

minimum read mapping quality (MAPQ)

yes

basequal

integer

minimum base-call quality (Phred-scaled)

yes

data

yes

. name

string

run name; results are written to results//

yes

. dnaseq

[‘object’, ‘null’]

DNA-seq inputs, one entry per group (group name -> read path(s))

yes

. rnaseq

[‘object’, ‘null’]

RNA-seq inputs, one entry per group (group name -> read path(s))

yes

. normal

[‘string’, ‘null’]

group name(s) of the matched normal/control sample

yes

. custom

yes

. . variants

[‘string’, ‘null’]

optional path to a user-supplied VCF to prioritize directly

yes

. . hlatyping

yes

. . . MHC-I

[‘string’, ‘null’]

yes

. . . MHC-II

[‘string’, ‘null’]

yes

preproc

yes

. activate

boolean

yes

. minlen

integer

discard reads shorter than this (bp) after trimming

yes

. slidingwindow

yes

. . activate

boolean

yes

. . wsize

integer

yes

. . wqual

integer

yes

align

yes

. chimSegmentMin

integer

yes

. chimScoreMin

integer

yes

. chimJunctionOverhangMin

integer

yes

. chimScoreDropMax

integer

yes

. chimScoreSeparation

integer

yes

altsplicing

yes

. activate

boolean

yes

. confidence

integer

yes

. iterations

integer

yes

. edgelimit

integer

yes

exitronsplicing

yes

. activate

boolean

yes

. ao

integer

yes

. pso

number

yes

. strand

integer

yes

genefusion

yes

. activate

boolean

yes

. maxevalue

number

yes

. suppreads

integer

yes

. maxsuppreads

integer

yes

. maxidentity

number

yes

. hpolymerlen

integer

yes

. readthroughdist

integer

yes

. minanchorlen

integer

yes

. splicedevents

integer

yes

. maxkmer

number

yes

. fraglen

integer

yes

. maxmismatch

number

yes

indel

yes

. activate

boolean

yes

. type

string

yes

. mode

string

yes

. strategy

string

yes

. fscorebeta

number

yes

. fdr

number

yes

. sliplen

integer

yes

. sliprate

number

yes

quantification

yes

. mode

string

yes

hlatyping

yes

. class

string

yes

. MHC-I_mode

string

DNA, RNA, or custom (comma-separated combinations allowed)

yes

. MHC-II_mode

string

yes

. freqdata

string

yes

. split

string

yes

. dict

string

yes

prioritization

yes

. class

string

yes

. lengths

yes

. . MHC-I

string

comma-separated epitope lengths

yes

. . MHC-II

string

yes

Linting and formatting

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