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@ -29,7 +29,7 @@ The pipeline is built using [Nextflow](https://www.nextflow.io/) and processes d
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- [Centrifuge](#centrifuge) - Taxonomic classifier that uses a novel indexing scheme based on the Burrows-Wheeler transform (BWT) and the Ferragina-Manzini (FM) index.
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- [Centrifuge](#centrifuge) - Taxonomic classifier that uses a novel indexing scheme based on the Burrows-Wheeler transform (BWT) and the Ferragina-Manzini (FM) index.
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- [Kaiju](#kaiju) - Taxonomic classifier that finds maximum (in-)exact matches on the protein-level.
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- [Kaiju](#kaiju) - Taxonomic classifier that finds maximum (in-)exact matches on the protein-level.
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- [Diamond](#diamond) - Sequence aligner for protein and translated DNA searches.
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- [Diamond](#diamond) - Sequence aligner for protein and translated DNA searches.
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- [MALT](#malt) - Sequence alignment and analysis tool designed for processing high-throughput sequencing data, especially in the context of metagenomics
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- [MALT](#malt) - Sequence alignment and analysis tool designed for processing high-throughput sequencing data, especially in the context of metagenomics
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- [MetaPhlAn3](#metaphlan3) - Genome-level marker gene based taxonomic classifier
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- [MetaPhlAn3](#metaphlan3) - Genome-level marker gene based taxonomic classifier
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- [mOTUs](#motus) - Tool for marker gene-based OTU (mOTU) profiling.
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- [mOTUs](#motus) - Tool for marker gene-based OTU (mOTU) profiling.
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- [MultiQC](#multiqc) - Aggregate report describing results and QC from the whole pipeline
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- [MultiQC](#multiqc) - Aggregate report describing results and QC from the whole pipeline
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@ -80,10 +80,10 @@ It is used in nf-core/taxprofiler for adapter trimming of short-reads.
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- `adapterremoval/`
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- `adapterremoval/`
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- `<sample_id>.settings`: AdapterRemoval log file containing general adapter removal, read trimming and merging statistics
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- `<sample_id>.settings`: AdapterRemoval log file containing general adapter removal, read trimming and merging statistics
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- `<sample_id>.collapsed.fastq.gz` - read-pairs that merged and did not undergo trimming (only when `--shortread_qc_mergepairs` supplied)
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- `<sample_id>.collapsed.fastq.gz` - read-pairs that merged and did not undergo trimming (only when `--shortread_qc_mergepairs` supplied)
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- `<sample_id>.collapsed.truncated.fastq.gz` - read-pairs that merged underwent quality trimming (only when `--shortread_qc_mergepairs` supplied)
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- `<sample_id>.collapsed.truncated.fastq.gz` - read-pairs that merged underwent quality trimming (only when `--shortread_qc_mergepairs` supplied)
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- `<sample_id>.pair1.truncated.fastq.gz` - read 1 of pairs that underwent quality trimming
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- `<sample_id>.pair1.truncated.fastq.gz` - read 1 of pairs that underwent quality trimming
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- `<sample_id>.pair2.truncated.fastq.gz` - read 2 of pairs that underwent quality trimming (and could not merge if `--shortread_qc_mergepairs` supplied)
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- `<sample_id>.pair2.truncated.fastq.gz` - read 2 of pairs that underwent quality trimming (and could not merge if `--shortread_qc_mergepairs` supplied)
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- `<sample_id>.singleton.truncated.fastq.gz` - orphaned read pairs where one of the pair was discarded
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- `<sample_id>.singleton.truncated.fastq.gz` - orphaned read pairs where one of the pair was discarded
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- `<sample_id>.discard.fastq.gz` - reads that were discarded due to length or quality filtering
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- `<sample_id>.discard.fastq.gz` - reads that were discarded due to length or quality filtering
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@ -133,7 +133,7 @@ It is used in nf-core/taxprofiler for complexity filtering using different algor
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- `prinseqplusplus/`
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- `prinseqplusplus/`
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- `<sample_id>.log`: log file containing number of reads. Row IDs correspond to: `min_len, max_len, min_gc, max_gc, min_qual_score, min_qual_mean, ns_max_n, noiupac, derep, lc_entropy, lc_dust, trim_tail_left, trim_tail_right, trim_qual_left, trim_qual_right, trim_left, trim_right`
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- `<sample_id>.log`: log file containing number of reads. Row IDs correspond to: `min_len, max_len, min_gc, max_gc, min_qual_score, min_qual_mean, ns_max_n, noiupac, derep, lc_entropy, lc_dust, trim_tail_left, trim_tail_right, trim_qual_left, trim_qual_right, trim_left, trim_right`
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- `<sample_id>_good_out.fastq.gz`: resulting FASTQ file without low-complexity reads
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- `<sample_id>_good_out.fastq.gz`: resulting FASTQ file without low-complexity reads
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</details>
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</details>
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@ -170,7 +170,7 @@ It is used with nf-core/taxprofiler to allow removal of 'host' (e.g. human) or o
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</details>
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</details>
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By default nf-core/taxprofiler will only provide the `.log` file if host removal is turned on. You will only see the mapped (host) reads BAM file or the off-target reads in FASTQ format in your results directory if you provide `--save_hostremoval_mapped` and ` --save_hostremoval_unmapped` respectively.
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By default nf-core/taxprofiler will only provide the `.log` file if host removal is turned on. You will only see the mapped (host) reads BAM file or the off-target reads in FASTQ format in your results directory if you provide `--save_hostremoval_mapped` and ` --save_hostremoval_unmapped` respectively.
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Note that the FASTQ file(s) may _not_ always be the 'final' reads that go into taxprofiling, if you also run other steps such as host removal, run merging etc..
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Note that the FASTQ file(s) may _not_ always be the 'final' reads that go into taxprofiling, if you also run other steps such as host removal, run merging etc..
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@ -235,7 +235,7 @@ The main taxonomic profiling file from Bracken is the `*.tsv` file. This provide
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</details>
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</details>
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The main taxonomic profiling file from Kraken2 is the `_combined_reports.txt` or `*report.txt` file. The former provides you the broadest over view of the taxonomic profiling results across all samples against a single databse, where you get two columns for each sample e.g. `2_all` and `2_lvl`, as well as a summarised column summing up across all samples `tot_all` and `tot_lvl`. The latter gives you the most information for a single sample. The report file is also used for the taxpasta step.
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The main taxonomic profiling file from Kraken2 is the `_combined_reports.txt` or `*report.txt` file. The former provides you the broadest over view of the taxonomic profiling results across all samples against a single databse, where you get two columns for each sample e.g. `2_all` and `2_lvl`, as well as a summarised column summing up across all samples `tot_all` and `tot_lvl`. The latter gives you the most information for a single sample. The report file is also used for the taxpasta step.
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You will only recieve the FASTQs and `*classifiedreads.txt` file if you supply `--kraken2_save_reads` and/or `--kraken2_save_readclassification` parameters to the pipeline.
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You will only recieve the FASTQs and `*classifiedreads.txt` file if you supply `--kraken2_save_reads` and/or `--kraken2_save_readclassification` parameters to the pipeline.
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@ -261,7 +261,6 @@ The main taxonomic profiling file from KrakenUniq is the `*report.txt` file. Thi
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You will only receive the FASTQs and `*classifiedreads.txt` file if you supply `--krakenuniq_save_reads` and/or `--krakenuniq_save_readclassification` parameters to the pipeline.
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You will only receive the FASTQs and `*classifiedreads.txt` file if you supply `--krakenuniq_save_reads` and/or `--krakenuniq_save_readclassification` parameters to the pipeline.
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### Centrifuge
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### Centrifuge
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[Centrifuge](https://github.com/DaehwanKimLab/centrifuge) is a taxonomic sequence classifier that uses a Burrows-Wheeler transform and Ferragina-Manzina index for storing and mapping sequences.
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[Centrifuge](https://github.com/DaehwanKimLab/centrifuge) is a taxonomic sequence classifier that uses a Burrows-Wheeler transform and Ferragina-Manzina index for storing and mapping sequences.
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@ -312,7 +311,7 @@ You will only receive the FASTQs and `*classifiedreads.txt` file if you supply `
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- `malt/`
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- `malt/`
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- `<db_name>/`
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- `<db_name>/`
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- `<sample_id>.blastn.sam`: sparse SAM file containing alignments of each hit
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- `<sample_id>.blastn.sam`: sparse SAM file containing alignments of each hit
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- `<sample_id>.megan`: summary file that can be loaded into the [MEGAN6](https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/algorithms-in-bioinformatics/software/megan6/) interactive viewer. Generated by MEGAN6 companion tool `rma2info`
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- `<sample_id>.megan`: summary file that can be loaded into the [MEGAN6](https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/algorithms-in-bioinformatics/software/megan6/) interactive viewer. Generated by MEGAN6 companion tool `rma2info`
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- `<sample_id>.rma6`: binary file containing all alignments and taxonomic information of hits that can be loaded into the [MEGAN6](https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/algorithms-in-bioinformatics/software/megan6/) interactive viewer
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- `<sample_id>.rma6`: binary file containing all alignments and taxonomic information of hits that can be loaded into the [MEGAN6](https://uni-tuebingen.de/fakultaeten/mathematisch-naturwissenschaftliche-fakultaet/fachbereiche/informatik/lehrstuehle/algorithms-in-bioinformatics/software/megan6/) interactive viewer
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- `<sample_id>.txt.gz`: text file containing taxonomic IDs and read counts against each taxon. Generated by MEGAN6 companion tool `rma2info`
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- `<sample_id>.txt.gz`: text file containing taxonomic IDs and read counts against each taxon. Generated by MEGAN6 companion tool `rma2info`
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@ -322,7 +321,6 @@ The main output of MALT is the `.rma6` file format, which can be only loaded int
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You will only recieve the `.sam` and `.megan` files if you supply `--malt_save_reads` and/or `--malt_generate_megansummary` parameters to the pipeline.
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You will only recieve the `.sam` and `.megan` files if you supply `--malt_save_reads` and/or `--malt_generate_megansummary` parameters to the pipeline.
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### MetaPhlAn3
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### MetaPhlAn3
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[MetaPhlAn3](https://github.com/biobakery/metaphlan) is a computational tool for profiling the composition of microbial communities (Bacteria, Archaea and Eukaryotes) from metagenomic shotgun sequencing data (i.e. not 16S) with species-level resolution via marker genes.
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[MetaPhlAn3](https://github.com/biobakery/metaphlan) is a computational tool for profiling the composition of microbial communities (Bacteria, Archaea and Eukaryotes) from metagenomic shotgun sequencing data (i.e. not 16S) with species-level resolution via marker genes.
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- `metaphlan3_<db_name>_combined_reports.txt`: A combined profile of all samples aligned to a given database (as generated by `metaphlan_merge_tables`)
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- `metaphlan3_<db_name>_combined_reports.txt`: A combined profile of all samples aligned to a given database (as generated by `metaphlan_merge_tables`)
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- `<db_name>/`
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- `<db_name>/`
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- `<sample_id>.biom`: taxonomic profile in BIOM format
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- `<sample_id>.biom`: taxonomic profile in BIOM format
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- `<sample_id>.bowtie2out.txt`: BowTie2 alignment information (can be re-used for skipping alignment when re-running MetaPhlAn3 with different parameters)
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- `<sample_id>.bowtie2out.txt`: BowTie2 alignment information (can be re-used for skipping alignment when re-running MetaPhlAn3 with different parameters)
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- `<sample_id>_profile.txt`: MetaPhlAn3 taxonomic profile including abundance estimates
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- `<sample_id>_profile.txt`: MetaPhlAn3 taxonomic profile including abundance estimates
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</details>
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</details>
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The main taxonomic profiling file from MetaPhlAn3 is the `*_profile.txt` file. This provides the abundance estimates from MetaPhlAn3 however does not include raw counts by default.
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The main taxonomic profiling file from MetaPhlAn3 is the `*_profile.txt` file. This provides the abundance estimates from MetaPhlAn3 however does not include raw counts by default.
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### mOTUs
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### mOTUs
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[mOTUS](https://github.com/motu-tool/mOTUs) maps reads to a unique marker specific database and estimates the relative abundance of known and unknown species.
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[mOTUS](https://github.com/motu-tool/mOTUs) maps reads to a unique marker specific database and estimates the relative abundance of known and unknown species.
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Please see the [KrakenUniq documentation](https://github.com/fbreitwieser/krakenuniq#database-building) for more information.
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Please see the [KrakenUniq documentation](https://github.com/fbreitwieser/krakenuniq#database-building) for more information.
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#### MALT custom database
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#### MALT custom database
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MALT does not provide any default databases for profiling, therefore you must build your own.
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MALT does not provide any default databases for profiling, therefore you must build your own.
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```bash
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```bash
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malt-build -i <path>/<to>/<fasta>/*.{fna,fa,fasta} -a2t <path>/<to>/<map>.db -d <YOUR_DB_NAME>/ -s DNA
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malt-build -i <path>/<to>/<fasta>/*.{fna,fa,fasta} -a2t <path>/<to>/<map>.db -d <YOUR_DB_NAME>/ -s DNA
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````
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```
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You can then add the <YOUR_DB_NAME>/ path to your nf-core/taxprofiler database input sheet.
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You can then add the <YOUR_DB_NAME>/ path to your nf-core/taxprofiler database input sheet.
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