HTS (NGS) 関連のインフォマティクス情報についてまとめています。

腫瘍全ゲノムの体細胞変異エンリッチメント解析のための柔軟なツールセット MutEnricher



 本著者らは、WGSデータからコーディングおよびノンコーディングゲノム領域における体細胞突然変異のエンリッチメントを調査するための柔軟なツールセットであるMutEnricherを紹介する。MutEnricher には、これらの目的のために 2 つの異なるモジュールが含まれており、サンプルおよびフィーチャー固有のバックグラウンド変異率を計算するためのカスタマイズ可能なオプションを提供する。さらに、両方の MutEnricher モジュールは、フィーチャー レベルおよびローカル (「ホットスポット」) の体細胞変異エンリッチメント統計値を計算する。

 MutEnricherは、体細胞突然変異のエンリッチメントを調査するための柔軟なソフトウェアパッケージで、Pythonで実装され、自由に利用でき、効率的に並列化でき、研究者の特定のニーズに合わせて高度に設定可能である。MutEnricherは、 からオンラインで入手できる。







MutEnricherは、全ゲノムシーケンス(WGS)データからタンパク質コードおよび非コードゲノム座の体細胞変異エンリッチメント解析を行う柔軟なツールセットで、Pythonで実装されており、Python 2および3で使用可能です。MutEnricherは、Dockerイメージとしても提供されています。MutEnricherは、2つの異なるモジュールを含んでいます。

  • coding - タンパク質コーディング遺伝子における非サイレント変異の体細胞エンリッチメント解析を実行する。
  • noncoding - 非コード領域のエンリッチメント解析を行う。





  • This software has been explicitly tested with Python 2.7 (versions 2.7.12 and greater) and Python 3.7 (versions 3.7.3) on Red Hat >=6, Ubuntu 16 LTS, and macOS Sierra. Compatibility with Python versions < 2.7 is likely possible, though untested


#docker (link)
docker pull asoltis/mutenricher:latest

> coding -h

usage: python coding [-h] [-o OUTDIR] [--prefix PREFIX]

                                    [--gene-field GENEFIELD] [-g GENE_LIST]

                                    [--stat-type STAT_TYPE]

                                    [--bg-vars-type BG_VARS_TYPE] [--maf MAF]

                                    [--exome-only] [--anno-type TTYPE]

                                    [-m MAP_REGIONS] [-p NPROCESSORS]

                                    [--snps-only] [-c COV_FN] [-w WEIGHTS_FN]

                                    [--by-contig] [--use-local]

                                    [--min-clust-size MIN_CLUST_SIZE]

                                    [--precomputed-covars COV_PRECOMP_DIR]

                                    [-d MAX_HS_DIST]

                                    [--min-hs-vars MIN_HS_VARS]

                                    [--min-hs-samps MIN_HS_SAMPS]

                                    [--blacklist BLACKLIST_FN]

                                    [--ap-iters AP_ITERS]

                                    [--ap-convits AP_CONVITS]

                                    [--ap-algorithm AP_ALG]

                                    genes.gtf vcfs_list.txt


positional arguments:

  genes.gtf             Input GTF file (Required). Can be provided as plain

                        text or gzip-compressed file.

  vcfs_list.txt         Input VCFs list file (Required). Required columns:

                        file path, sample name. NOTE: sample names must be

                        unique for each sample!


optional arguments:

  -h, --help            show this help message and exit

  -o OUTDIR, --outdir OUTDIR

                        Provide output directory for analysis. (default: ./)

  --prefix PREFIX       Provide prefix for analysis. (default:


  --gene-field GENEFIELD

                        Provide field name from input GTF containing gene

                        name/id information. (default: gene_id)

  -g GENE_LIST, --gene-list GENE_LIST

                        Provide list of genes to which analysis should be

                        restricted (one gene per-line in text file). Analysis

                        will only considers genes from GTF file that are

                        present in this list. Default behavior is to query all

                        coding genes present in input GTF. (default: None)

  --stat-type STAT_TYPE

                        Select the stype of statistical testing to perform.

                        Options are: 1) 'nsamples' (default), which uses the

                        binomial distribution to compute the significance of

                        the number of samples containing a non-silent somatic

                        mutation ('n') among 'N' total samples against

                        background mutation rate 'p', or 2) 'nmutations',

                        which uses the negative binomial distribution to

                        compute the significance of the number of non-silent

                        mutations 'k' in a gene of coding length 'x' against

                        background mutation rate 'p' (default: nsamples)

  --bg-vars-type BG_VARS_TYPE

                        Select which variants should be counted in background

                        rate calculations. Choices are: 'all' and 'silent'. If

                        'all' is selected, all variants (silent + non-silent)

                        are counted in background calculations. If 'silent' is

                        selected, only silent mutations count towards

                        background. (default: all)

  --maf MAF             Instead of VCF list file, provide MAF (mutation

                        annotation format) file with mutation information. To

                        use, provide a dummy character (e.g. "-") for the VCFs

                        argument and provide a MAF file with this option. Gene

                        information (e.g. lengths) are computed from input

                        GTF. Genes not present by genefield in GTF (read from

                        first column of MAF) are skipped. Input MAF can be

                        provided as plain text of gzip-compressed file.

                        (default: None)

  --exome-only          If using exome-based data, choose this flag to only

                        consider exonic coordinates of genes for background

                        estimates. Default behavior is to consider full gene

                        length (exons + introns) in calculations. (default:


  --anno-type TTYPE     Select annotation type for determining non-silent

                        somatic variants. Valid pre-sets are: 'annovar-

                        refGene', 'annovar-knownGene', 'annovar-ensGene',

                        'SnpEff', 'VEP', or 'illumina'. For 'illumina', 'CSQT'

                        INFO field is parsed; for 'SnpEff', 'ANN' INFO field

                        is parsed. For 'VEP', the CSQ INFO field is parsed.

                        Alternatively, provide tab-delimited input text file

                        describing terms for use. If providing text file, must

                        include one term per row with 3 columns: 1) String

                        that is either 'Gene' or 'Effect' to denote field with

                        gene name or gene effect, respectively; 2) value from

                        VCF INFO field for code to search for matching gene

                        name or non-silent effect; 3) valid terms (can be left

                        blank for 'Gene' row). If MAF input is used, this

                        option is ignored and default MAF terms are used.

                        (default: annovar-refGene)

  -m MAP_REGIONS, --mappable-regions MAP_REGIONS

                        Provide BED file of mappable genomic regions (sorted

                        and tabix-indexed). If provided, only portions of

                        regions from input file overlapping these mappable

                        regions will be used in analsyis. Region lengths are

                        also adjusted for enrichment calculations. (default:



                        Set number of processors for parallel runs. (default:


  --snps-only           Set this flag to tell program to only consider SNPs in

                        analysis. Default is to consider all variant types.

                        (default: False)

  -c COV_FN, --covariates-file COV_FN

                        Provide covariates file. Format is tab-delimited text

                        file, with first column listing gene name according to

                        gene_id field in input GTF. Header should contain

                        covariate names in columns 2 to end. (default: None)

  -w WEIGHTS_FN, --covariate-weights WEIGHTS_FN

                        Provide covariates weight file. Format is tab-

                        delimited file (no header) with: covariate name,

                        weight. Weights are normalized to sum=1. If not

                        provided, uniform weighting of covariates is assumed.

                        (default: None)

  --by-contig           Use this flag to perform clustering on genes by contig

                        (i.e. by chromosome). This speeds computation of gene

                        clusters. If not set, clusters are computed using all

                        genes in same run. (default: False)

  --use-local           Use this flag to tell the program to use the local

                        gene background rate instead of global background

                        rate. If covariate files or pre-computed covariates

                        are supplied along with this flag being set, a

                        combined covariate plus local background scheme is

                        used whereby local backgrounds from cluster members

                        are considered. (default: False)

  --min-clust-size MIN_CLUST_SIZE

                        Set minimum number of covariate cluster members.

                        Regions belonging to a cluster with only itself or

                        less than this value are flagged and a local

                        background around the region is calculated and used

                        instead. (default: 3)

  --precomputed-covars COV_PRECOMP_DIR

                        Provide path to pre-computed covariate clusters for

                        genes in input GTF file. (default: None)

  -d MAX_HS_DIST, --hotspot-distance MAX_HS_DIST

                        Set maximum distance between mutations for candidate

                        hotspot discovery. (default: 50)

  --min-hs-vars MIN_HS_VARS

                        Set minimum number of mutations that must be present

                        for a valid candidate hotspot. (default: 3)

  --min-hs-samps MIN_HS_SAMPS

                        Set minimum number of samples that must contain

                        mutations to inform a valid candidate hotspot.

                        (default: 2)

  --blacklist BLACKLIST_FN

                        Provide a blacklist of specific variants to exclude

                        from analysis. Blacklist file format is tab-delimited

                        text file with four required columns: contig

                        (chromosome), position (1-indexed), reference base,

                        alternate base. (default: None)

  --ap-iters AP_ITERS   Set maximum number of AP iterations before re-

                        computing with alternate self-similarity. (default:


  --ap-convits AP_CONVITS

                        Set number of convergence iterations for AP runs (i.e.

                        if exemplars remain constant for this many iterations,

                        terminate early). This value MUST be smaller than the

                        total number of iterations. (default: 50)

  --ap-algorithm AP_ALG

                        Select between one of two versions of AP clustering

                        algorithm: 'slow' or 'fast'. The 'fast' version is

                        faster in terms of runtime but consumes more memory

                        than 'slow'. (default: fast)






git clone
cd MutEnricher/example_data/




ls vcfs/*.vcf.gz | while read VCF; do
name=$(basename $VCF .vcf.gz)
echo -e "/data/$VCF\t$name" >> test_vcf_paths.txt

> head test_vcf_paths.txt


3、MutEnricher codingをランする。VCFのリストとBEDファイル、もしくはgtf.ファイルを指定する。

mkdir out
sudo docker run -itv $PWD:/data -v $PWD/out:/tmp --rm asoltis/mutenricher python noncoding /data/annotation_files/ucsc.refFlat.20170829.promoters_up2kb_downUTR.no_chrMY.bed /data/test_vcf_paths.txt -o /tmp --prefix noncoding_example_global_bg









MutEnricher: a flexible toolset for somatic mutation enrichment analysis of tumor whole genomes
Anthony R Soltis, Clifton L Dalgard, Harvey B Pollard, Matthew D Wilkerson 

BMC Bioinformatics. 2020 Jul 31;21(1):338