Skip to content

Latest commit

 

History

History
243 lines (205 loc) · 10.2 KB

cookbook.md

File metadata and controls

243 lines (205 loc) · 10.2 KB
Raw

Table of Contents

Introduction & Installation

This cookbook walks you through a variety of applications of minimap2 and its companion script paftools.js. All data here are freely available from the minimap2 release page at version tag v2.10. Some examples only work with v2.10 or later.

To acquire the data used in this cookbook and to install minimap2 and paftools, please follow the command lines below:

# install minimap2 executables
curl -L https://github.com/lh3/minimap2/releases/download/v2.24/minimap2-2.24_x64-linux.tar.bz2 | tar jxf -
cp minimap2-2.24_x64-linux/{minimap2,k8,paftools.js} .  # copy executables
export PATH="$PATH:"`pwd`                               # put the current directory on PATH
# download example datasets
curl -L https://github.com/lh3/minimap2/releases/download/v2.10/cookbook-data.tgz | tar zxf -

Mapping Genomic Reads

Mapping long reads

minimap2 -ax map-pb -t4 ecoli_ref.fa ecoli_p6_25x_canu.fa > mapped.sam

Alternatively, you can create a minimap2 index first and then map:

minimap2 -x map-pb -d ecoli-pb.mmi ecoli_ref.fa                      # create an index
minimap2 -ax map-pb ecoli-pb.mmi ecoli_p6_25x_canu.fa > mapped.sam

This will save you a couple of minutes when you map against the human genome. HOWEVER, key algorithm parameters such as the k-mer length and window size can't be changed after indexing. Minimap2 will give you a warning if parameters used in a pre-built index doesn't match parameters on the command line. Please always make sure you are using an intended pre-built index.

Mapping Illumina paired-end reads:

minimap2 -ax sr -t4 ecoli_ref.fa ecoli_mason_1.fq ecoli_mason_2.fq > mapped-sr.sam

Evaluating mapping accuracy with simulated reads (for developers)

minimap2 -ax sr ecoli_ref.fa ecoli_mason_1.fq ecoli_mason_2.fq | paftools.js mapeval -

The output is:

Q       60      19712   0       0.000000000     19712
Q       0       282     219     0.010953286     19994
U       6

where a U-line gives the number of unmapped reads (for SAM input only); a Q-line gives:

  1. Mapping quality (mapQ) threshold
  2. Number of mapped reads between this threshold and the previous mapQ threshold.
  3. Number of wrong mappings in the same mapQ interval
  4. Accumulative mapping error rate
  5. Accumulative number of mappings

For paftools.js mapeval to work, you need to encode the true read positions in read names in the right format. For pbsim2 and mason2, we provide scripts to generate the right format. Simulated reads in this cookbook were created with the following command lines:

# in the pbsim2 source code directory:
src/pbsim --depth 1 --length-min 5000 --length-mean 20000 --accuracy-mean 0.95 --hmm_model data/R94.model ../ecoli_ref.fa
paftools.js pbsim2fq ../ecoli_ref.fa.fai sd_0001.maf > ../ecoli_pbsim.fa

# mason2 simulation
mason_simulator --illumina-prob-mismatch-scale 2.5 -ir ecoli_ref.fa -n 10000 -o tmp-l.fq -or tmp-r.fq -oa tmp.sam
paftools.js mason2fq tmp.sam | seqtk seq -1 > ecoli_mason_1.fq
paftools.js mason2fq tmp.sam | seqtk seq -2 > ecoli_mason_2.fq

Mapping Long RNA-seq Reads

Mapping Nanopore 2D cDNA reads

minimap2 -ax splice SIRV_E2.fa SIRV_ont-cdna.fa > aln.sam

You can compare the alignment to the true annotations with:

paftools.js junceval SIRV_E2C.gtf aln.sam

It gives the percentage of introns found in the annotation. For SIRV data, it is possible to achieve higher junction accuracy with

minimap2 -ax splice --splice-flank=no SIRV_E2.fa SIRV_ont-cdna.fa | paftools.js junceval SIRV_E2C.gtf

This is because minimap2 models one additional evolutionarily conserved base around a canonical junction, but SIRV doesn't honor this signal. Option --splice-flank=no asks minimap2 no to model this additional base.

In the output a tag ts:A:+ indicates that the read strand is the same as the transcript strand; ts:A:- indicates the read strand is opposite to the transcript strand. This tag is inferred from the GT-AG signal and is thus only available to spliced reads.

Mapping Nanopore direct-RNA reads

minimap2 -ax splice -k14 -uf SIRV_E2.fa SIRV_ont-drna.fa > aln.sam

Direct-RNA reads are noisier, so we use a shorter k-mer for improved sensitivity. Here, option -uf forces minimap2 to map reads to the forward transcript strand only because direct-RNA reads are stranded. Again, applying --splice-flank=no helps junction accuracy for SIRV data.

Mapping PacBio Iso-seq reads

minimap2 -ax splice -uf -C5 SIRV_E2.fa SIRV_iso-seq.fq > aln.sam

Option -C5 reduces the penalty on non-canonical splicing sites. It helps to align such sites correctly for data with low error rate such as Iso-seq reads and traditional cDNAs. On this example, minimap2 makes one junction error. Applying --splice-flank=no fixes this alignment error.

Note that the command line above is optimized for the final Iso-seq reads. PacBio's Iso-seq pipeline produces intermediate sequences at varying quality. For example, some intermediate reads are not stranded. For these reads, option -uf will lead to more errors. Please revise the minimap2 command line accordingly.

Full-Genome Alignment

Intra-species assembly alignment

# option "--cs" is recommended as paftools.js may need it
minimap2 -cx asm5 --cs ecoli_ref.fa ecoli_canu.fa > ecoli_canu.paf

Here ecoli_canu.fa is the Canu assembly of ecoli_p6_25x_canu.fa. This command line outputs alignments in the PAF format. Use -a instead of -c to get output in the SAM format.

Cross-species full-genome alignment

minimap2 -cx asm20 --cs ecoli_ref.fa ecoli_O104:H4.fa > ecoli_O104:H4.paf
sort -k6,6 -k8,8n ecoli_O104:H4.paf | paftools.js call -f ecoli_ref.fa -L10000 -l1000 - > out.vcf

Minimap2 has three presets for full-genome alignment: "asm5" for sequence divergence below 1%, "asm10" for divergence around a couple of percent and "asm20" for divergence not more than 10%. In theory, with the right setting, minimap2 should work for sequence pairs with sequence divergence up to ~15%, but this has not been carefully evaluated.

Eyeballing alignment

# option "--cs" required; minimap2-r741 or higher required for the "asm20" preset
minimap2 -cx asm20 --cs ecoli_ref.fa ecoli_O104:H4.fa | paftools.js view - | less -S

This prints the alignment in a BLAST-like format.

Calling variants from assembly-to-reference alignment

# don't forget the "--cs" option; otherwise it doesn't work
minimap2 -cx asm5 --cs ecoli_ref.fa ecoli_canu.fa \
  | sort -k6,6 -k8,8n \
  | paftools.js call -f ecoli_ref.fa - > out.vcf

Without option -f, paftools.js call outputs in a custom format. In this format, lines starting with R give the regions covered by one contig only. This information is not available in the VCF output.

Constructing self-homology map

minimap2 -DP -k19 -w19 -m200 ecoli_ref.fa ecoli_ref.fa > out.paf

Option -D asks minimap2 to ignore anchors from perfect self match and -P outputs all chains. For large nomes, we don't recommend to perform base-level alignment (with -c, -a or --cs) when -P is applied. This is because base-alignment is slow and occasionally gives wrong alignments close to the diagonal of a dotter plot. For E. coli, though, base-alignment is still fast.

Lift over (for developers)

minimap2 -cx asm5 --cs ecoli_ref.fa ecoli_canu.fa > ecoli_canu.paf
echo -e 'tig00000001\t200000\t300000' | paftools.js liftover ecoli_canu.paf -

This lifts over a region on query sequences to one or multiple regions on reference sequences. Note that this paftools.js command may not be efficient enough to lift millions of regions.

Read Overlap

Long read overlap

# For pacbio reads:
minimap2 -x ava-pb ecoli_p6_25x_canu.fa ecoli_p6_25x_canu.fa > overlap.paf
# For Nanopore reads (ava-ont also works with PacBio but not as good):
minimap2 -x ava-ont -r 10000 ecoli_p6_25x_canu.fa ecoli_p6_25x_canu.fa > overlap.paf
# If you have miniasm installed:
miniasm -f ecoli_p6_25x_canu.fa overlap.paf > asm.gfa

Here we explicitly applied -r 10000. We are considering to set this as the default for the ava-ont mode as this seems to improve the contiguity for nanopore read assembly (Loman, personal communication).

Minimap2 doesn't work well with short-read overlap.

Evaluating overlap sensitivity (for developers)

# read to reference mapping
minimap2 -cx map-pb ecoli_ref.fa ecoli_p6_25x_canu.fa > to-ref.paf
# evaluate overlap sensitivity
sort -k6,6 -k8,8n to-ref.paf | paftools.js ov-eval - overlap.paf

You can see that for PacBio reads, minimap2 achieves higher overlap sensitivity with -x ava-pb (99% vs 93% with -x ava-ont).