nf-core/eager

You will need to create a design file with information about the samples in your experiment before running the pipeline. Use this parameter to specify its location. It has to be a comma-separated file with 3 columns, and a header row. See usage docs.

Set this parameter to your e-mail address to get a summary e-mail with details of the run sent to you when the workflow exits. If set in your user config file ( ~/.nextflow/config) then you don't need to specify this on the command line for every run.

This parameter is *mandatory* if --genome is not specified. If you don't supply a mapper index (e.g. for BWA), this will be generated for you automatically. Combine with --save_reference to save mapper index for future runs.

If you want to use a pre-existing samtools faidx index, use this to specify the required FASTA index file for the selected reference genome. This should be generated by samtools faidx and has a file suffix of .fai.

If you want to use a pre-existing picard CreateSequenceDictionary dictionary file, use this to specify the required .dict file for the selected reference genome.

For most people this will likely be the same directory that contains the file you provided to --fasta.

If you want to use pre-existing bwa index indices, the directory should contain files ending in '.amb' '.ann' '.bwt'. If you want to use pre-existing bowtie2 build indices, the directory should contain files ending in'.1.bt2', '.2.bt2', '.rev.1.bt2'.

In any case do not include the files themselves in the path. nf-core/eager will automagically detect the index files by searching for the FASTA filename with the corresponding bwa index/ bowtie2 build file suffixes. If not supplied, the indices will be generated for you.

Use this if you do not have pre-made reference FASTA indices for bwa, samtools and picard. If you turn this on, the indices nf-core/eager generates for you and will be saved in the <your_output_dir>/results/reference_genomes for you. If not supplied, nf-core/eager generated index references will be deleted.

modifies SAMtools index command: -c

The entry (chromosome, contig, etc.) in your FASTA reference that you'd like to be treated as circular.

Applies only when providing a single FASTA file via --fasta (NOT multi-reference input - see reference TSV/CSV input).

Modifies tool parameter(s):

• circulargenerator -s

Specify the FASTA entry in the reference file specified as --fasta that acts as the mitochondrial 'chromosome' to base a mitochondrial-to-nuclear ratio calculation on.

The tool only accepts the first section of the header before the first space. For example, mitochondrion chromosome name is MT for the hs37d5/GrCH37 human reference genome.

Specify which tool to use for sequencing quality control.

Falco is designed as a drop-in replacement for FastQC but written in C++ for faster computation. We recommend using falco with very large datasets (due to reduced memory constraints).

Specify to skip all preprocessing steps (adapter removal, paired-end merging, poly-g trimming etc).

This will also mean you will only get one set of FastQC results (of the input reads).

Specify which preprocessing tool to use.

AdapterRemoval is commonly used in palaeogenomics, however fastp has similar performance and has many additional functionality (including inbuilt complexity trimming) that can be often useful.

Turns off the paired-end read merging, and will result in paired-end mapping modes being used during reference of reads again alignment.

This can be useful in cases where you have long ancient DNA reads, modern DNA, or when you want to utilise mate-pair 'spatial' information..

⚠️ If you run this and also with --preprocessing_minlength set to a value (as is by default!), you may end up removing single reads from either the pair1 or pair2 file. These reads will be NOT be mapped when aligning with either bwa or bowtie, as both can only accept one (forward) or two (forward and reverse) FASTQs as input in paired-end mode.

⚠️ If you run metagenomic screening as well as skipping merging, all reads will be screened as independent reads - not as pairs! - as all FASTQ files from BAM filtering are merged into one. This merged file is not saved in results directory.

Modifies AdapterRemoval parameter: --collapse
Modifies fastp parameter: --merge

Specify to exclude pairs that did not overlap sufficiently for merging (i.e., keep merged reads only), in otherwords singletons (i.e. reads missing a pair), or un-merged reads (where there wasn't sufficient overlap) are discarded.

Most ancient DNA molecules are very short, and the majority are expected to merge. Specifying this parameter can sometimes be useful when dealing with ultra-short aDNA reads to reduce the number of longer-reads you may have in your library that are derived from modern contamination. It can also speed up run time of mapping steps.

You may want to use this if you want ensure only the best quality reads for your analysis, but with the penalty of potentially losing still valid data (even if some reads have slightly lower quality and/or are longer). It is highly recommended when using 'dedup' deduplication tool.

Specify to turn off trimming of adapters from reads.

You may wish to do this if you are using public data (e.g. ENA, SRA), that should have all library artefacts from reads.

This will override any other adapter parameters provided (i.e, --preprocessing_adapterlist and or/ --preprocessing_adapter{1,2} will be ignored)!

Modifies AdapterRemoval parameter: --adapter1 and --adapter2 (sets both to an empty string)
Applies fastp parameter: --disable_adapter_trimming

Specify a nucleotide sequence for the forward read/R1.

If not modified by the user, the default for the particular preprocessing tool will be used. Therefore, to turn off adapter trimming use --preprocessing_skipadaptertrim.

Modifies AdapterRemoval parameter: --adapter1
Modifies fastp parameter: --adapter_sequence

Specify a nucleotide sequence for the forward read/R2.

If not modified by the user, the default for the particular preprocessing tool will be used. To turn off adapter trimming use --preprocessing_skipadaptertrim.

Modifies AdapterRemoval parameter: --adapter2
Modifies fastp parameter: --adapter_sequence_r2

Allows to supply a file with a list of adapter (combinations) to remove from all files.

Overrides the --preprocessing_adapter1/ --preprocessing_adapter2 parameters .

Note that the two tools have slightly different behaviours.

For AdapterRemoval this consists of a two column table with a .txt extension: first column represents forward strand, second column for reverse strand. You must supply all possibly combinations, one per line, and this list is applied to all files. Only Adapters in this list will be screened for and removed. See AdapterRemoval documentation for more information.

For fastp this consists of a standard FASTA format with a .fasta/ .fa/ .fna/ .fas extension. The adapter sequence in this file should be at least 6bp long, otherwise it will be skipped. fastp first will perform auto-detection of reads and will be removed , and then additionally adapters present in the FASTA file one by one will be removed.

Modifies AdapterRemoval parameter: --adapter-list
Modifies fastp parameter: --adapter_fasta

Specify the minimum length reads must have to be retained.

Reads smaller than this length after trimming are discarded and not included in downstream analyses. Typically in ancient DNA users will set this to 30 or for very old samples around 25 bp - reads any shorter that this often are not specific enough to provide useful information.

Modifies AdapterRemoval parameter: --minlength
Modifies fastp parameter: --length_required

Specify number of bases to hard-trim from 5 prime or front of reads. Exact behaviour varies per tool, see documentation. By default set to 0 to not perform any hard trimming.

This parameter allows users to 'hard' remove a number of bases from the beginning or end of reads, regardless of quality.

⚠️ when this trimming occurs depends on the tool, i.e., the exact behaviour is not the same between AdapterRemoval and fastp.

For fastp: this 5p/3p trimming occurs prior to any other trimming (quality, poly-G, adapter). Please see the fastp documentation for more information. If you wish to use this to remove damage prior mapping (to allow more specific mapping), ensure you have manually removed adapters/quality trimmed * prior* to giving the reads to nf-core/eager. Alternatively, you can use Bowtie2's inbuilt pre-mapping read-end trimming functionality. Note that nf-core/eager only allows this hard trimming equally for both forward and reverse reads (i.e., you cannot provide different values for the 5p end for R1 and R2).

For AdapterRemoval, this trimming happens after the removal of adapters, however prior to quality trimming. Therefore this is more suitable for hard-removal of damage prior mapping (however the Bowtie2 system will be more reliable).

Modifies AdapterRemoval parameters: --trim5p
Modifies fastp parameters: --trim_front1 and/or --trim_front2

Specify number of bases to hard-trim from 3 prime or tail of reads. Exact behaviour varies per tool, see documentation. By default set to 0 to not perform any hard trimming.

This parameter allows users to 'hard' remove a number of bases from the beginning or end of reads, regardless of quality.

⚠️ when this trimming occurs depends on the tool, i.e., the exact behaviour is not the same between AdapterRemoval and fastp.

For fastp: this 5p/3p trimming occurs prior to any other trimming (quality, poly-G, adapter). Please see the fastp documentation for more information. If you wish to use this to remove damage prior mapping (to allow more specific mapping), ensure you have manually removed adapters/quality trimmed * prior* to giving the reads to nf-core/eager. Alternatively, you can use Bowtie2's inbuilt pre-mapping read-end trimming functionality. Note that nf-core/eager only allows this hard trimming equally for both forward and reverse reads (i.e., you cannot provide different values for the 3p end for R1 and R2).

For AdapterRemoval, this trimming happens after the removal of adapters, however prior to quality trimming. Therefore this is more suitable for hard-removal of damage prior mapping (however the Bowtie2 system will be more reliable).

Modifies AdapterRemoval parameters: --trim3p
Modifies fastp parameters: --trim_tail1 and/or --trim_tail2

Specify to save the preprocessed reads in FASTQ format the results directory.

This can be useful for re-analysing in FASTQ files manually, or uploading to public data repositories such as ENA/SRA (provided you don't do length filtering nor merging).

Performs a poly-G tail removal step in the beginning of the pipeline using fastp.

This can be useful for trimming ploy-G tails from short-fragments sequenced on two-colour Illumina chemistry such as NextSeqs or NovaSeqs (where no-fluorescence is read as a G on two-colour chemistry), which can inflate reported GC content values.

Modifies fastp parameter: --trim_poly_g

This option can be used to define the minimum length of a poly-G tail to begin low complexity trimming.

Modifies fastp parameter: --poly_g_min_len

Turns off quality based trimming at the 5p end of reads when any of the AdapterRemoval quality or N trimming options are used. Only 3p end of reads will be removed.

This also entirely disables quality based trimming of collapsed reads, since both ends of these are informative for PCR duplicate filtering. For more information see the AdapterRemoval documentation.

Modifies AdapterRemoval parameters: --preserve5p

Turns off AdapterRemoval quality trimming from ends of reads.

This can be useful to reduce runtime when running public data that has already been processed.

Modifies AdapterRemoval parameters: --trimqualities

Defines the minimum read quality per base that is required for a base to be kept. Individual bases at the ends of reads falling below this threshold will be clipped off.

Modifies AdapterRemoval parameter: --minquality

Turns off AdapterRemoval N trimming from ends of reads.

This can be useful to reduce runtime when running public data that has already been processed.

Modifies AdapterRemoval parameters: --trimns

Specifies a minimum number of bases that overlap with the adapter sequence before AdapterRemoval trims adapters sequences from reads.

Modifies AdapterRemoval parameter: --minadapteroverlap

Specify maximum Phred score of the quality field of FASTQ files.

The quality-score range can vary depending on the machine and version (e.g. see diagram here, and this allows you to increase from the default AdapterRemoval value of 41.

Note that while this theoretically can provide you with more confident and precise base call information, many downstream tools only accept FASTQ files with Phred scores limited to a max of 41, and therefore increasing the default for this parameter may make the resulting preprocessed files incompatible with some downstream tools.

Modifies AdapterRemoval parameters: --qualitymax

Specify which mapping tool to use. Options are BWA aln (' bwaaln'), BWA mem (' bwamem'), circularmapper (' circularmapper'), or bowtie2 (' bowtie2'). BWA aln is the default and highly suited for short-read ancient DNA. BWA mem can be quite useful for modern DNA, but is rarely used in projects for ancient DNA. CircularMapper enhances the mapping procedure to circular references, using the BWA algorithm but utilizing a extend-remap procedure (see Peltzer et al 2016, Genome Biology for details). Bowtie2 is similar to BWA aln, and has recently been suggested to provide slightly better results under certain conditions ( Poullet and Orlando 2020), as well as providing extra functionality (such as FASTQ trimming).

More documentation can be seen for each tool under:

• BWA aln
• BWA mem
• CircularMapper
• Bowtie2

This parameter is required to be set for large reference genomes. If your reference genome is larger than 3.5GB, the samtools index calls in the pipeline need to generate .csi indices instead of .bai indices to compensate for the size of the reference genome (with samtools: -c). This parameter is not required for smaller references (including the human hg19 or grch37/grch38 references), but >4GB genomes have been shown to need .csi indices.

Configures the bwa aln -n parameter, defining how many mismatches are allowed in a read. Default is set following recommendations from Oliva et al. 2021 who tested when aligning to human reference genomes.

If you're uncertain what to set check out this Shiny App for more information on how to set this parameter efficiently.

Modifies bwa aln parameter: -n

Configures the bwa aln -k parameter for the maximum edit distance during the seeding phase of the mapping algorithm.

Modifies BWA aln parameter: -k

Configures the length of the seed used in bwa aln -l. Default is set to be 'turned off' at the recommendation of Oliva et al. 2021 who tested when aligning to human reference genomes. Seeding is 'turned off' by specifying an arbitrarily long number to force the entire read to act as the seed.

Note: Despite being recommended, turning off seeding can result in long runtimes!

Modifies BWA aln parameter: -l

Configures the number of gaps used in bwa aln. Default is set to bwa default.

Modifies BWA aln parameter: -o

Configures the minimum seed length used in BWA-MEM. Default is set to BWA default.

Modifies BWA-MEM parameter: -k

Configures the re-seeding used in BWA-MEM. Default is set to BWA default.

Modifies BWA-MEM parameter: -r

The type of read alignment to use. Local allows only partial alignment of read, with ends of reads possibly 'soft-clipped' (i.e. remain unaligned/ignored), if the soft-clipped alignment provides best alignment score. End-to-end requires all nucleotides to be aligned.
Default is set following Cahill et al (2018) and Poullet and Orlando 2020

Modifies Bowtie2 presets: --local, --end-to-end

The Bowtie2 'preset' to use. These strings apply to both --mapping_bowtie2_alignmode options. See the Bowtie2 manual for actual settings.
Default is set following Poullet and Orlando (2020), when running damaged-data without UDG treatment)

Modifies the Bowtie2 parameters: --fast, --very-fast, --sensitive, --very-sensitive, --fast-local, --very-fast-local, --sensitive-local, --very-sensitive-local

The number of mismatches allowed in the seed during seed-and-extend procedure of Bowtie2. This will override any values set with --mapping_bowtie2_sensitivity. Can either be 0 or 1.

Modifies Bowtie2 parameter: -N

The length of the seed sub-string to use during seeding. This will override any values set with --mapping_bowtie2_sensitivity.

Modifies Bowtie2 parameter: -L

Number of bases to trim at the 5' (left) end of read prior alignment. Maybe useful when left-over sequencing artefacts of in-line barcodes present.

Modifies Bowtie2 parameter: --trim5

Number of bases to trim at the 3' (right) end of read prior alignment. Maybe useful when left-over sequencing artefacts of in-line barcodes present.

Modifies Bowtie2 parameter: --trim3

The maximum fragment for valid paired-end alignments. Only for paired-end mapping (i.e. unmerged), and therefore typically only useful for modern data.

Modifies Bowtie2 parameter: --maxins

Turns on the filtering subworkflow for mapped BAM files coming out of the read alignment step. Filtering includes removal of unmapped reads, length filtering, and mapping quality filtering.

When turning on bam filtering, by default only the mapped/unmapped filter is activated, thus only mapped reads are retained for downstream analyses. See --bamfiltering_retainunmappedgenomicbam to retain unmapped reads, if filtering only for length and/or quality is preferred.

Note this subworkflow can also be activated if --run_metagenomic_screening is supplied.

You can use this to remove mapped reads that fall below a certain length after mapping.

This can be useful to get more realistic 'endogenous DNA' or 'on target read' percentages.

If used instead of minimum length read filtering at AdapterRemoval, you can get more more realistic endogenous DNA estimates when most of your reads are very short (e.g. in single-stranded libraries or samples with highly degraded DNA). In these cases, the default minimum length filter at earlier adapter clipping/read merging will remove a very large amount of your reads in your library (including valid reads), thus making an artificially small denominator for a typical endogenous DNA calculation.

Therefore by retaining all of your reads until after mapping (i.e., turning off the adapter clipping/read merging filter), you can generate more 'real' endogenous DNA estimates immediately after mapping (with a better denominator). Then after estimating this, filter using this parameter to retain only 'useful' reads (i.e., those long enough to provide higher confidence of their mapped position) for downstream analyses.

By specifying 0, no length filtering is performed.

Note that by default the output BAM files of this step are not stored in the results directory (as it is assumed that deduplicated BAM files are preferred). See --bamfiltering_savefilteredbams if you wish to save these.

Modifies tool parameter(s):

• filter_bam_fragment_length.py: -l

Specify a mapping quality threshold for mapped reads to be kept for downstream analysis.

By default all reads are retained and is therefore set to 0 to ensure no quality filtering is performed.

Note that by default the output BAM files of this step are not stored in the results directory (as it is assumed that deduplicated BAM files are preferred). See --bamfiltering_savefilteredbams if you wish to save these.

Modifies tool parameter(s):

• samtools view -q

You can use this to customise the exact SAM format flag of reads you wish to remove from your BAM file to for downstream genomic analyses.

You can explore more using a tool from the Broad institute here

⚠️ Modify at your own risk, alternative flags are not necessarily supported in downstream steps!

Modifies tool parameter(s):
- SAMtools: -F

You can use this parameter to retain unmapped reads (optionally also length filtered) in the genomic BAM for downstream analysis. By default, the pipeline only keeps mapped reads for downstream analysis.

This is also turned on if --metagenomicscreening_input is set to all.

⚠️ This will likely slow down run time of downstream pipeline steps!

Modifies tool parameter(s):

• samtools view: -f 4 / -F 4

This turns on the generation and saving of FASTQs of only the unmapped reads from the mapping step in the results directory, using samtools fastq.

This could be useful if you wish to do other analysis of the unmapped reads independently of the pipeline.

Note: the reads in these FASTQ files have not undergone length of quality filtering

Modifies tool parameter(s):

• samtools fastq: -f 4

This turns on the generation and saving of FASTQs of only the mapped reads from the mapping step in the results directory, using samtools fastq.

This could be useful if you wish to do other analysis of the mapped reads independently of the pipeline, such as remapping with different parameters (whereby only including mapped reads will speed up computation time during the re-mapping due to reduced input data).

Note the reads in these FASTQ files have not undergone length of quality filtering

Modifies tool parameter(s):

• samtools fastq: -F 4

This saves intermediate length and/or quality filtered genomic BAM files in the results directory.

Turns on the metagenomic screening subworkflow of the pipeline, where reads are screened against large databases. Typically used for pathogen screening or microbial community analysis.

If supplied, this will also turn on the BAM filtering subworkflow of the pipeline.

You can select which reads coming out of the read alignment step will be sent for metagenomic analysis.

This influences which reads are sent to this step, whether you want unmapped reads (used in most cases, as 'host reads' can often be contaminants in microbial genomes), mapped reads (e.g, when doing competitive against a genomic reference of multiple genomes and which to apply LCA correction), or all reads.

⚠️ If you skip paired-end merging, all reads will be screened as independent reads - not as pairs! - as all FASTQ files from BAM filtering are merged into one. This merged file is not saved in results directory.

Modifies tool parameter(s):

• samtools fastq: -f 4 / -F 4

Turns on a subworkflow of the pipeline that filters the fastq-files for complexity before the metagenomics profiling
Use the metagenomics_complexity_tool parameter to select a method

Save the complexity-filtered fastq-files to the results directory

You can select which tool is used to generate a final set of reads for the metagenomic classifier after any necessary trimming, filtering or reformatting of the reads.

This intermediate file is not saved in the results directory, unless marked with --metagenomics_complexity_savefastq.

Specify the minimum 'entropy' value for complexity filtering for the BBDuk or PRINSEQ++ tools.

This value will only be used for PRINSEQ++ if --metagenomics_prinseq_mode is set to entropy.

Entropy here corresponds to the amount of sequence variation exists within the read. Higher values correspond to more variety, and thus will likely result in more specific matching to a taxon's reference genome. The trade off here is fewer reads (or abundance information) available for having a confident identification.

Modifies tool parameter(s):

• BBDuk: entropy=
• PRINSEQ++: -lc_entropy

Specify the complexity filter mode for PRINSEQ++

Use the selected mode together with the correct flag:
'dust' requires the --metagenomics_prinseq_dustscore parameter set
'entropy' requires the --metagenomics_complexity_entropy parameter set

Sets one of the tool parameter(s):

• PRINSEQ++: -lc_entropy
• PRINSEQ++: -lc_dust

Specify the minimum dust score below which low-complexity reads will be removed. A DUST score is based on how often different tri-nucleotides occur along a read.

Modifies tool parameter(s):

• PRINSEQ++: --lc_dust

Sets the duplicate read removal tool. Alternatively an ancient DNA specific read deduplication tool dedup (Peltzer et al. 2016) is offered. The latter utilises both ends of paired-end data to remove duplicates (i.e. true exact duplicates, as markduplicates will over-zealously deduplicate anything with the same starting position even if the ends are different).

⚠️ DeDup can only be used on collapsed (i.e. merged) reads from paired-end sequencing.

Turns on mapDamage2's BAM rescaling functionality. This probabilistically replaces Ts back to Cs depending on the likelihood this reference-mismatch was originally caused by damage. If the library is specified to be single stranded, this will automatically use the --single-stranded mode.
This process will ameliorate the effects of aDNA damage, but also increase reference-bias.

* This functionality does not have any MultiQC output.*
warning: rescaled libraries will not be merged with non-scaled libraries of the same sample for downstream genotyping, as the model may be different for each library. If you wish to merge these, please do this manually and re-run nf-core/eager using the merged BAMs as input.

Modifies the --rescale parameter of mapDamage2

Specify the length in bp from the end of the read that mapDamage should rescale at both ends.

Modifies the --seq-length parameter of mapDamage2.

Specify the length in bp from the end of the read that mapDamage should rescale. Overrides --rescale_seqlength.

Modifies the --rescale-length-5p parameter of mapDamage2.

Specify the length in bp from the end of the read that mapDamage should rescale. Overrides --rescale_seqlength.

Modifies the --rescale-length-3p parameter of mapDamage2.

Specifies to run PMDtools for damage based read filtering in sequencing libraries.

Specifies the PMDScore threshold to use in the pipeline when filtering BAM files for DNA damage. Only reads which surpass this damage score are considered for downstream DNA analysis.

Modifies PMDtools parameter: --threshold

Supplying a bedfile to this parameter activates masking of the reference fasta at the contained sites prior to running PMDtools. Positions that are in the provided bedfile will be replaced by Ns in the reference genome.
This can alleviate reference bias when running PMD filtering on capture data, where you might not want the allele of a transition SNP to be counted as damage. Masking of the reference is done using bedtools maskfasta.

Turns on the BAM trimming method. Trims off [n] bases from reads in the deduplicated BAM file. Damage assessment in PMDtools or DamageProfiler remains untouched, as data is routed through this independently. BAM trimming is typically performed to reduce errors during genotyping that can be caused by aDNA damage.

BAM trimming will only affect libraries with 'damage_treatment' of 'none' or 'half'. Complete UDG treatment ('full') should have removed all damage, during library construction so trimming of 0 bp is performed. The amount of bases that will be trimmed off from each side of the molecule should be set separately for libraries with depending on their 'strandedness' and 'damage_treatment'.

Note: additional artefacts such as bar-codes or adapters should be removed prior to mapping and not in this step.

Default is set to 0, and therefore clips off no bases on the left side of reads from double-stranded libraries whose UDG treatment is set to'none'. Note that reverse reads will automatically be clipped off at the reverse side with this (automatically reverses left and right for the reverse read).

Modifies bamUtil's trimBam parameter: -L

Default is set to 0, and therefore clips off no bases on the right side of reads from double-stranded libraries whose UDG treatment is set to'none'. Note that reverse reads will automatically be clipped off at the reverse side with this (automatically reverses left and right for the reverse read).

Modifies bamUtil's trimBam parameter: -R

Default is set to 0, and therefore clips off no bases on the left side of reads from double-stranded libraries whose UDG treatment is set to 'half'. Note that reverse reads will automatically be clipped off at the reverse side with this (automatically reverses left and right for the reverse read).

Modifies bamUtil's trimBam parameter: -L

Default is set to 0, and therefore clips off no bases on the right side of reads from double-stranded libraries whose UDG treatment is set to 'half'. Note that reverse reads will automatically be clipped off at the reverse side with this (automatically reverses left and right for the reverse read).

Modifies bamUtil's trimBam parameter: -R

Default is set to 0, and therefore clips off no bases on the left side of reads from single-stranded libraries whose UDG treatment is set to 'none'. Note that reverse reads will automatically be clipped off at the reverse side with this (automatically reverses left and right for the reverse read).

Modifies bamUtil's trimBam parameter: -L

Default is set to 0, and therefore clips off no bases on the right side of reads from single-stranded libraries whose UDG treatment is set to 'none'. Note that reverse reads will automatically be clipped off at the reverse side with this (automatically reverses left and right for the reverse read).

Modifies bamUtil's trimBam parameter: -R

Default is set to 0, and therefore clips off no bases on the left side of reads from single-stranded libraries whose UDG treatment is set to 'half'. Note that reverse reads will automatically be clipped off at the reverse side with this (automatically reverses left and right for the reverse read).

Modifies bamUtil's trimBam parameter: -L

Default is set to 0, and therefore clips off no bases on the right side of reads from single-stranded libraries whose UDG treatment is set to 'half'. Note that reverse reads will automatically be clipped off at the reverse side with this (automatically reverses left and right for the reverse read).

Modifies bamUtil's trimBam parameter: -R

By default, nf-core/eager uses hard trimming, which sets trimmed bases to 'N' with quality '!' in the BAM output. Turn this on to use soft-trimming instead, which masks reads at the read ends using the CIGAR string instead.

Modifies bam trimBam parameter: -c

Indicates which BAM file to use for genotyping, depending on what BAM processing modules you have turned on. Options are: 'raw' (to use the reads used as input for damage manipulation); 'pmd' (for pmdtools output); 'trimmed' (for base-clipped BAMs. Base-clipped-PMD-filtered BAMs if both filtering and trimming are requested); 'rescaled' (for mapDamage2 rescaling output).
Warning: Depending on the parameters you provided, 'raw' can refer to all mapped reads, filtered reads (if bam filtering has been performed), or the deduplicated reads (if deduplication was performed).

Turn on the module to estimate the ratio of mitochondrial to nuclear reads.

Specify the FASTA entry in the reference file specified as --fasta, which acts as the mitochondrial 'chromosome' to base the ratio calculation on. The tool only accepts the first section of the header before the first space. The default chromosome name is based on hs37d5/GrCH37 human reference genome.

Turns off the computation of library complexity estimation.

Specify which mode of preseq to run.

From the PreSeq documentation:

c curve is used to compute the expected complexity curve of a mapped read file with a hypergeometric formula

lc extrap is used to generate the expected yield for theoretical larger experiments and bounds on the number of distinct reads in the library and the associated confidence intervals, which is computed by bootstrapping the observed duplicate counts histogram.

Can be used to configure the step size of Preseq's c_curve and lc_extrap method. Can be useful when few reads and allow Preseq to be used for extrapolation of shallow sequencing results.

Modifies tool parameter(s)

• preseq: -s

Specify the maximum number of terms that lc_extrap mode will use.

Modifies preseq lc_extrap parameter: -x

Specify the maximum extrapolation that lc_extrap mode will perform.

Modifies preseq lc_extrap parameter: -e

Specify the number of bootstraps lc_extrap mode will perform to calculate confidence intervals.

Modifies preseq lc_extrap parameter: -n

Specify the allowed level of confidence intervals used for lc_extrap mode.

Modifies preseq lc_extrap parameter: -c

Activates defects mode of lc_extrap, which does the extrapolation without testing for defects.

Modifies preseq lc_extrap parameter: -D

Turns off the DamageProfiler module to compute DNA damage profiles.

Modifies DamageProfile parameter: -l

Specifies the length of the read start and end to be considered for profile generation in DamageProfiler.

Modifies DamageProfile parameter: -t

Specifies what the maximum misincorporation frequency should be displayed as, in the DamageProfiler damage plot. This is set to 0.30 (i.e. 30%) by default as this matches the popular mapDamage2.0 program. However, the default behavior of the DamageProfiler is to 'autoscale' the y-axis maximum to zoom in on any possible damage that may occur (e.g. if the damage is about 10%, the highest value on the y-axis would be set to 0.12). This 'autoscale' behavior can be turned on by specifying the number to 0.

Modifies DamageProfile parameter: -yaxis_dp_max

Specifies to turn on the bedtools module, producing statistics for breadth (or percent coverage), and depth (or X fold) coverages.

Modifies tool parameter(s):

• bedtools coverage: -mean

Specify the path to a GFF/BED containing the feature coordinates (or any acceptable input for bedtools coverage). Must be in quotes.

Recreates pre-adapter-removal and/or read-pair-merging FASTQ files but without reads that mapped to reference (e.g. for public upload of privacy-sensitive non-host data)

Modifies extract_map_reads.py parameter: -m

Specify to run the optional processes for nuclear DNA contamination estimation with ANGSD.

The name of the chromosome as specified in your FASTA/bam header.
e.g. 'X' for hs37d5, 'chrX' for HG19

The beginning of the genetic range that should be utilised for nuclear contamination estimation.

The end of the genetic range that should be utilised for nuclear contamination estimation.

Modifies angsd parameter: -minMapQ

Modifies angsd parameter: -minQ

The haplotype map, or "HapMap", records the location of haplotype blocks and their tag SNPs.