Now MutMap is updated for easier installation and utilization using Python platform.
Citation: Abe, A. et al. (2012) Genome sequencing reveals agronomically important loci in rice using MutMap. Nature Biotechnol. 30:174-179.
- matplotlib
- numpy
- pandas
- seaborn (optional)
You can install MutMap using bioconda.
$ conda install -c bioconda mutmap
If you got a error during installation, you can install MutMap, manually.
$ git clone https://github.com/YuSugihara/MutMap.git
$ cd MutMap
$ pip install -e .
Then you have to install other dependencies by yourself. We highly recommend you to install SnpEff and Trimmomatic using bioconda.
$ conda install -c bioconda snpeff
$ conda install -c bioconda triimomatic
After installation, please check whether SnpEff and Trimmomatic work through the commands below.
$ snpEff --help
$ trimmomatic --help
$ mutmap -h
usage: mutmap -r <FASTA> -c <BAM|FASTQ> -b <BAM|FASTQ>
-n <INT> -o <OUT_DIR> [-T] [-e <DATABASE>]
MutMap version 2.1.1
optional arguments:
-h, --help show this help message and exit
-r , --ref Reference fasta.
-c , --cultivar fastq or bam of cultivar. If you specify
fastq, please separate pairs by commma,
e.g. -c fastq1,fastq2. You can use this
optiion multiple times
-b , --bulk fastq or bam of mutnat bulk. If you specify
fastq, please separate pairs by commma,
e.g. -b fastq1,fastq2. You can use this
optiion multiple times
-n , --N-bulk Number of individuals in mutant bulk.
-o , --out Output directory. Specified name must not
exist.
-t , --threads Number of threads. If you specify the number
below one, then MutMap will use the threads
as many as possible. [2]
-w , --window Window size (kb). [2000]
-s , --step Step size (kb). [100]
-D , --max-depth Maximum depth of variants which will be used.
This cutoff will be applied in both of cultivar
and bulk. [250]
-d , --min-depth Minimum depth of variants which will be used.
This cutoff will be applied in both of cultivar
and bulk. [8]
-N , --N-rep Number of replicates for simulation to make
null distribution. [5000]
-T, --trim Trim fastq using trimmomatic.
-a , --adapter FASTA of adapter sequences. This will be used
when you specify "-T" for trimming.
--trim-params Parameters for trimmomatic. Input parameters
must be separated by comma with following
order: phred, ILLUMINACLIP, LEADING, TRAILING,
SLIDINGWINDOW, MINLEN. If you want to remove
adapters of illumina, please specify FASTA of
the adapter sequences with "--adapter". Specified
name will be inserted into <ADAPTER_FASTA>. If you
don't specify it, adapter trimming will be skipped.
[33,<ADAPTER_FASTA>:2:30:10,20,20,4:15,75]
-e , --snpEff Predict causal variant using SnpEff. Please
check available databases in SnpEff.
--mem Maximum memory per thread when bam sorted;
suffix K/M/G recognized. [1G]
-q , --min-MQ Minimum mapping quality in mpileup. [40]
-Q , --min-BQ Minimum base quality in mpileup. [18]
-C , --adjust-MQ "adjust-MQ" in mpileup. Default parameter
is suited for BWA. [50]
-v, --version show program's version number and exit
MutMap can run from FASTQ (without or with trimming) and BAM. If you want to run MutMap from VCF, please use MutPlot (example 5). Once you run MutMap, MutMap automatically complete the subprocesses.
- Example 1 : run MutMap from FASTQ without trimming
- Example 2 : run MutMap from FASTQ with trimming
- Example 3 : run MutMap from BAM
- Example 4 : run MutMap from multiple FASTQs and BAMs
- Example 5 : run MutPlot from VCF
$ mutmap -r reference.fasta \
-c cultivar.1.fastq,cultivar.2.fastq \
-b bulk.1.fastq,bulk.2.fastq \
-n 20 \
-o example_dir
-r : reference fasta
-c : FASTQs of cultivar. Please input pair-end reads separated by comma. FASTQs can be gzipped.
-b : FASTQs of bulk. Please input pair-end reads separated by comma. FASTQs can be gzipped.
-n : number of individuals in mutant bulk.
-o : name of output directory. Specified name cannot exist.
$ mutmap -r reference.fasta \
-c cultivar.1.fastq,cultivar.2.fastq \
-b bulk.1.fastq,bulk.2.fastq \
-n 20 \
-o example_dir \
-T
-r : reference fasta
-c : FASTQs of cultivar. Please input pair-end reads separated by comma. FASTQs can be gzipped.
-b : FASTQs of bulk. Please input pair-end reads separated by comma. FASTQs can be gzipped.
-n : number of individuals in mutant bulk.
-o : name of output directory. Specified name cannot exist.
-T : trim your reads by triimomatic.
$ mutmap -r reference.fasta \
-c cultivar.bam \
-b bulk.bam \
-n 20 \
-o example_dir
-r : reference fasta
-c : BAM of cultivar.
-b : BAM of bulk.
-n : number of individuals in mutant bulk.
-o : name of output directory. Specified name cannot exist.
$ mutmap -r reference.fasta \
-c cultivar_1.1.fastq,cultivar_1.2.fastq \
-c cultivar_1.bam \
-b bulk_1.1.fastq,bulk_1.2.fastq \
-b bulk_2.bam \
-b bulk_3.bam \
-n 20 \
-o example_dir
MutMap can automatically merge multiple FASTQs and BAMs. Of course, you can merge FASTQs or BAMs using cat or samtools merge before input them to MutMap. If you specify -c multiple times, please make sure that those files include only 1 individual. On the other hand, -b can include more than 1 individuals because those are bulked samples. MutMap can automatically classify FASTQs and BAMs from whether comma exits or not.
$ mutplot -h
usage: mutplot -v <VCF> -o <OUT_DIR> -n <INT> [-w <INT>] [-s <INT>]
[-D <INT>] [-d <INT>] [-N <INT>] [-m <FLOAT>]
[-S <INT>] [-e <DATABASE>] [--igv] [--indel]
MutPlot version 2.1.2
optional arguments:
-h, --help show this help message and exit
-v , --vcf VCF which contains cultivar and mutant bulk.
-o , --out Output directory. Specified name can exist.
-n , --N-bulk Number of individuals in mutant bulk.
-w , --window Window size (kb). [2000]
-s , --step Step size (kb). [100]
-D , --max-depth Maximum depth of variants which will be used.
This cutoff will be applied in both of cultivar
and bulk. [250]
-d , --min-depth Minimum depth of variants which will be used.
This cutoff will be applied in both of cultivar
and bulk. [8]
-N , --N-rep Number of replicates for simulation to make
null distribution. [5000]
-m , --min-SNPindex Cutoff of minimum SNP-index for clear results. [0.3]
-S , --strand-bias Filter spurious homo genotypes in cultivar using
strand bias. If ADF (or ADR) is higher than this
cutoff when ADR (or ADF) is 0, that SNP will be
filtered out. If you want to supress this filtering,
please set this cutoff to 0. [7]
-e , --snpEff Predict causal variant using SnpEff. Please
check available databases in SnpEff.
--igv Output IGV format file to check results on IGV.
--indel Plot SNP-index with INDEL.
--fig-width Width allocated in chromosome figure. [7.5]
--fig-height Height allocated in chromosome figure. [4.0]
--white-space White space between figures. (This option
only affect vertical direction.) [0.6]
--version show program's version number and exit
MutPlot is included in MutMap. MutMap run MutPlot after making VCF. Then, MutPlot will work with default parameters. If you want to change some parameters, you can use VCF inside of (OUT_DIR/30_vcf/mutmap.vcf.gz) to retry plotting process like below.
$ mutplot -v OUT_DIR/30_vcf/mutmap.vcf.gz \
-o ANOTHER_DIR_NAME \
-n 20 \
-w 2000 \
-s 100
In this case, please make sure that:
- Your VCF include AD format.
- Your VCF include two columns of cultivar and mutant bulk in this order.
If you got a error, please try to run MutMap from FASTQ or BAM before asking in issues.
Inside of OUT_DIR is like below.
|-- 10_ref
| |-- reference.fasta
| |-- reference.fasta.amb
| |-- reference.fasta.ann
| |-- reference.fasta.bwt
| |-- reference.fasta.fai
| |-- reference.fasta.pac
| `-- reference.fasta.sa
|-- 20_bam
| |-- bulk.filt.bam
| |-- bulk.filt.bam.bai
| |-- cultivar.filt.bam
| `-- cultivar.filt.bam.bai
|-- 30_vcf
| |-- mutmap.vcf.gz
| `-- mutmap.vcf.gz.tbi
|-- 40_mutmap
| |-- snp_index.tsv
| |-- sliding_window.tsv
| `-- mutmap_plot.png
`-- log
|-- bcftools.log
|-- bgzip.log
|-- bwa.log
|-- mutplot.log
|-- samtools.log
`-- tabix.log
- If you run MutMap with trimming, you will get the directory of
00_fastqwhich includes �FASTQs after trimming. - You can check the results in
40_mutmap.snp_index.tsv: columns in this order.- CHROM : chromosome name
- POSI : position in chromosome
- VARIANT : SNP or INDEL
- DEPTH : depth of bulk
- p99 : 99% confidence interval of simulated SNP-index
- p95 : 95% confidence interval of simulated SNP-index
- SNP-index : real SNP-index
sliding_window.tsv: columns in this order.- CHROM : chromosome name
- POSI : central position of window
- MEAN p99 : mean of p99
- MEAN p95 : mean of p95
- MEAN SNP-index : mean SNP-index
mutmap_plot.png: resulting plot- BLUE dot : variant
- RED line : mean SNP-index
- ORANGE line : mean p99
- GREEN line : mean p95
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