User guide

For up-to-date User Guides please see Lazypipe Wiki:

• Lazypipe User Guide v2.1
• Lazypipe User Guide v3.0
• Running Lazypipe on CSC Puhti

Example 1

In this example we will use a sample PE library that is included with the repository (data/samples/M15small_R*.fastq).

Preprocess reads with fastp:

perl lazypipe.pl -1 data/samples/M15small_R1.fastq --pipe pre -t 8 -v

Download Neovison vison genome and use it to filter host reads. Note that running host filtering with a newly downloaded genome will take some time to index the genome:

mkdir -p $data/hostgen

wget https://ftp.ncbi.nlm.nih.gov/genomes/all/GCA/900/108/605/GCA_900108605.1_NNQGG… -P $data/hostgen/

perl lazypipe.pl -1 data/samples/M15small_R1.fastq --pipe flt --hostgen $data/hostgen/GCA_900108605.1_NNQGG.v01_genomic.fna.gz -t 8 -v

Run assembling with Megahit and realign reads to assembly

perl lazypipe.pl -1 data/samples/M15small_R1.fastq -p ass,rea --ass megahit -t 8 -v

Run 1st round annotation with Minimap2 against your local minimap.refseq database:

perl lazypipe.pl -1 data/samples/M15small_R1.fastq -p ann1 --ann1 minimap.refseq -t 8 -v

Run 1st round annotation with SANSparallel against UniProt TrEMBL. Note that SANSparallel runs on a remote server and requires internet connection. Append results to Minimap2 annotations from the previous step:

perl lazypipe.pl -1 data/samples/M15small_R1.fastq -p ann1 --ann1 sans --append -t 8 -v

Now run a more complex 1st round annotation. Start by mapping contigs with Minimap2, then map unmapped contigs with SANSparallel, then map unmapped contigs with BLASTN against blastn.vi database. Note that without --append flag this will overwrite existing 1st round annotations:

perl lazypipe.pl -1 data/samples/M15small_R1.fastq -p ann1 --ann1 minimap.refseq,sans,blastn.vi -t 8 -v

Run 2nd round annotation. In the second round you can target archaeal+bacterial (=ab), bacteriophage (=ph), viral (=vi) and unmapped (=un) contigs, based on labeling from the 1st round. Local databases for the 2nd round annotations are defined in ann2.databases section of the config.yaml. For example, to map viral contigs with BLASTN and BLASTP against local viral databases type:

perl lazypipe.pl -1 data/samples/M15small_R1.fastq --pipe ann2 --ann2 blastn.vi.refseq,blastp.vi -t 8 -v

Run 2nd round annotation for bacteria with BLASTN. Append results to BLASTN and BLASTP annotations from the previous step:

perl lazypipe.pl -1 data/samples/M15small_R1.fastq --pipe ann2 --ann2 blastn.ab.refseq --append -t 8 -v

You can also combine these runs in any order. For example:

perl lazypipe.pl -1 data/samples/M15small_R1.fastq --pipe ann2 --ann2 blastn.ab.refseq,blastn.vi.refseq,blastp.vi -t 8 -v

The most common combinations of 1st and 2nd round annotations can be saved to config.yaml in the ann.strategies section. Each annotation strategy is saved as a key-value pair. There are several annotation strategies predifined:

• abv.fast -- run only the 1st round with Minimap2 against RefSeq.abv
• abv.nt -- 1st round: Minimap2 against NT.abv, 2nd round: BLASTN viral reads against NT.vi and archaeal+bacterial reads against NT.ab
• abv.refseq -- 1st round: Minimap2 against RefSeq.abv, 2nd round: BLASTN viral reads against RefSeq.vi and archaeal+bacterial reads against RefSeq.ab
• abv.extend -- 1st round: Minimap2 against NT.abv + SANSparallel unmapped reads against TrEMBL, 2nd round: BLASTN viral reads against NT.vi and archaeal+bacterial reads against NT.ab, additionally BLASTP viral reads against UniRef100.vi and archaeal+bacterial reads against UniRef100.ab
• vi.nt -- 1st round: Minimap2 against NT.vi, 2nd round: BLASTN viral reads against NT.vi
• vi.refseq -- 1st round: Minimap2 against RefSeq.vi, 2nd round: BLASTN viral reads against RefSeq.vi

Generate reports based on created annotations:

perl lazypipe.pl -1 data/samples/M15small_R1.fastq --pipe rep -t 8 -v

Generate assembly stats, pack for sharing and remove temporary files:

perl lazypipe.pl -1 data/samples/M15small_R1.fastq -p stats,pack,clean -t 8 -v

For convenience, routine analysis steps (pre,flt,ass,rea,ann1,ann2,rep,sta,pack,clean) can be called with maintag. To run main analysis with normal annotation strategy type:

perl lazypipe.pl -1 data/samples/M15small_R1.fastq -p main --anns norm -t 8 -v

Results are output to $res/$sample. Default value for $res is set in config.yaml and default value for $sample is created from the name of the input reads. These can be changed during runtime with --res mydir --sample mysample.

Assembled contigs and predicted ORFs

Table 1: Lazypipe results: contigs and ORFs.

Taxon Abundancies

Spreadsheets with taxon abundancies are printed to abund_table.xlsx. Abundancies are displayed in separate tables for viruses (excluding bacteriophages), bacteria, bacteriophages and eukaryots. For each domain abundancies are displayed at three taxonomic levels: species, genus and family.

For raw abundance data see abund_table.tsv.

Table 2: Columns in abund_table.xlsx

Contig Annotations

Spreadsheets with contig annotations are printed to contig_annot.xslx. Spreadsheets are displayed separately for viruses (excluding bacteriophages), bacteria, bacteriophages and eukaryots.

For raw annotation data see contigs_annot.tsv. 

Table 3: Columns in contigs_annot.xslx

Krona Graph and Quality Control Plots

Quality Control (QC) plots include length histograms for reads and contigs, and survival plots. The survival plots track retained reads after each pipeline step.

Table 4: Quality Control plots