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Sofia Stamouli 2023-01-17 15:50:10 +01:00
parent 024b683671
commit 4dcf8c0b02
2 changed files with 12 additions and 14 deletions

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@ -29,7 +29,7 @@ The pipeline is built using [Nextflow](https://www.nextflow.io/) and processes d
- [Centrifuge](#centrifuge) - Taxonomic classifier that uses a novel indexing scheme based on the Burrows-Wheeler transform (BWT) and the Ferragina-Manzini (FM) index. - [Centrifuge](#centrifuge) - Taxonomic classifier that uses a novel indexing scheme based on the Burrows-Wheeler transform (BWT) and the Ferragina-Manzini (FM) index.
- [Kaiju](#kaiju) - Taxonomic classifier that finds maximum (in-)exact matches on the protein-level. - [Kaiju](#kaiju) - Taxonomic classifier that finds maximum (in-)exact matches on the protein-level.
- [Diamond](#diamond) - Sequence aligner for protein and translated DNA searches. - [Diamond](#diamond) - Sequence aligner for protein and translated DNA searches.
- [MALT](#malt) - Sequence alignment and analysis tool designed for processing high-throughput sequencing data, especially in the context of metagenomics - [MALT](#malt) - Sequence alignment and analysis tool designed for processing high-throughput sequencing data, especially in the context of metagenomics
- [MetaPhlAn3](#metaphlan3) - Genome-level marker gene based taxonomic classifier - [MetaPhlAn3](#metaphlan3) - Genome-level marker gene based taxonomic classifier
- [mOTUs](#motus) - Tool for marker gene-based OTU (mOTU) profiling. - [mOTUs](#motus) - Tool for marker gene-based OTU (mOTU) profiling.
- [MultiQC](#multiqc) - Aggregate report describing results and QC from the whole pipeline - [MultiQC](#multiqc) - Aggregate report describing results and QC from the whole pipeline
@ -80,10 +80,10 @@ It is used in nf-core/taxprofiler for adapter trimming of short-reads.
- `adapterremoval/` - `adapterremoval/`
- `<sample_id>.settings`: AdapterRemoval log file containing general adapter removal, read trimming and merging statistics - `<sample_id>.settings`: AdapterRemoval log file containing general adapter removal, read trimming and merging statistics
- `<sample_id>.collapsed.fastq.gz` - read-pairs that merged and did not undergo trimming (only when `--shortread_qc_mergepairs` supplied) - `<sample_id>.collapsed.fastq.gz` - read-pairs that merged and did not undergo trimming (only when `--shortread_qc_mergepairs` supplied)
- `<sample_id>.collapsed.truncated.fastq.gz` - read-pairs that merged underwent quality trimming (only when `--shortread_qc_mergepairs` supplied) - `<sample_id>.collapsed.truncated.fastq.gz` - read-pairs that merged underwent quality trimming (only when `--shortread_qc_mergepairs` supplied)
- `<sample_id>.pair1.truncated.fastq.gz` - read 1 of pairs that underwent quality trimming - `<sample_id>.pair1.truncated.fastq.gz` - read 1 of pairs that underwent quality trimming
- `<sample_id>.pair2.truncated.fastq.gz` - read 2 of pairs that underwent quality trimming (and could not merge if `--shortread_qc_mergepairs` supplied) - `<sample_id>.pair2.truncated.fastq.gz` - read 2 of pairs that underwent quality trimming (and could not merge if `--shortread_qc_mergepairs` supplied)
- `<sample_id>.singleton.truncated.fastq.gz` - orphaned read pairs where one of the pair was discarded - `<sample_id>.singleton.truncated.fastq.gz` - orphaned read pairs where one of the pair was discarded
- `<sample_id>.discard.fastq.gz` - reads that were discarded due to length or quality filtering - `<sample_id>.discard.fastq.gz` - reads that were discarded due to length or quality filtering
@ -133,7 +133,7 @@ It is used in nf-core/taxprofiler for complexity filtering using different algor
- `prinseqplusplus/` - `prinseqplusplus/`
- `<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` - `<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`
- `<sample_id>_good_out.fastq.gz`: resulting FASTQ file without low-complexity reads - `<sample_id>_good_out.fastq.gz`: resulting FASTQ file without low-complexity reads
</details> </details>
@ -170,7 +170,7 @@ It is used with nf-core/taxprofiler to allow removal of 'host' (e.g. human) or o
</details> </details>
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. 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.
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.. 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..
@ -235,7 +235,7 @@ The main taxonomic profiling file from Bracken is the `*.tsv` file. This provide
</details> </details>
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. 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.
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. 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.
@ -261,7 +261,6 @@ The main taxonomic profiling file from KrakenUniq is the `*report.txt` file. Thi
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. 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.
### Centrifuge ### Centrifuge
[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. [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.
@ -312,7 +311,7 @@ You will only receive the FASTQs and `*classifiedreads.txt` file if you supply `
- `malt/` - `malt/`
- `<db_name>/` - `<db_name>/`
- `<sample_id>.blastn.sam`: sparse SAM file containing alignments of each hit - `<sample_id>.blastn.sam`: sparse SAM file containing alignments of each hit
- `<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` - `<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`
- `<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 - `<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
- `<sample_id>.txt.gz`: text file containing taxonomic IDs and read counts against each taxon. Generated by MEGAN6 companion tool `rma2info` - `<sample_id>.txt.gz`: text file containing taxonomic IDs and read counts against each taxon. Generated by MEGAN6 companion tool `rma2info`
@ -322,7 +321,6 @@ The main output of MALT is the `.rma6` file format, which can be only loaded int
You will only recieve the `.sam` and `.megan` files if you supply `--malt_save_reads` and/or `--malt_generate_megansummary` parameters to the pipeline. You will only recieve the `.sam` and `.megan` files if you supply `--malt_save_reads` and/or `--malt_generate_megansummary` parameters to the pipeline.
### MetaPhlAn3 ### MetaPhlAn3
[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. [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.
@ -334,12 +332,13 @@ You will only recieve the `.sam` and `.megan` files if you supply `--malt_save_r
- `metaphlan3_<db_name>_combined_reports.txt`: A combined profile of all samples aligned to a given database (as generated by `metaphlan_merge_tables`) - `metaphlan3_<db_name>_combined_reports.txt`: A combined profile of all samples aligned to a given database (as generated by `metaphlan_merge_tables`)
- `<db_name>/` - `<db_name>/`
- `<sample_id>.biom`: taxonomic profile in BIOM format - `<sample_id>.biom`: taxonomic profile in BIOM format
- `<sample_id>.bowtie2out.txt`: BowTie2 alignment information (can be re-used for skipping alignment when re-running MetaPhlAn3 with different parameters) - `<sample_id>.bowtie2out.txt`: BowTie2 alignment information (can be re-used for skipping alignment when re-running MetaPhlAn3 with different parameters)
- `<sample_id>_profile.txt`: MetaPhlAn3 taxonomic profile including abundance estimates - `<sample_id>_profile.txt`: MetaPhlAn3 taxonomic profile including abundance estimates
</details> </details>
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. 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.
### mOTUs ### mOTUs
[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. [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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@ -631,7 +631,6 @@ krakenuniq-build --db <DB_DIR_NAME> --kmer-len 31
Please see the [KrakenUniq documentation](https://github.com/fbreitwieser/krakenuniq#database-building) for more information. Please see the [KrakenUniq documentation](https://github.com/fbreitwieser/krakenuniq#database-building) for more information.
#### MALT custom database #### MALT custom database
MALT does not provide any default databases for profiling, therefore you must build your own. MALT does not provide any default databases for profiling, therefore you must build your own.
@ -640,7 +639,7 @@ In addition to the input directory, output directory, and the mapping file datab
```bash ```bash
malt-build -i <path>/<to>/<fasta>/*.{fna,fa,fasta} -a2t <path>/<to>/<map>.db -d <YOUR_DB_NAME>/ -s DNA malt-build -i <path>/<to>/<fasta>/*.{fna,fa,fasta} -a2t <path>/<to>/<map>.db -d <YOUR_DB_NAME>/ -s DNA
```` ```
You can then add the <YOUR_DB_NAME>/ path to your nf-core/taxprofiler database input sheet. You can then add the <YOUR_DB_NAME>/ path to your nf-core/taxprofiler database input sheet.