diff --git a/docs/usage.md b/docs/usage.md
index 8ec435a..36d3a8d 100644
--- a/docs/usage.md
+++ b/docs/usage.md
@@ -185,7 +185,7 @@ work                # Directory containing the nextflow working files
 
 ### Sequencing quality control
 
-nf-core taxprofiler offers [`falco`][https://github.com/smithlabcode/falco] as an alternative option to [`FastQC`](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/).
+nf-core taxprofiler offers [`falco`](https://github.com/smithlabcode/falco) as an alternative option to [`FastQC`](https://www.bioinformatics.babraham.ac.uk/projects/fastqc/).
 
 ### Preprocessing Steps
 
@@ -202,14 +202,14 @@ Raw sequencing read processing in the form of adapter clipping and paired-end re
 
 It is highly recommended to run this on raw reads to remove artifacts from sequencing that can cause false positive identification of taxa (e.g. contaminated reference genomes) and/or skews in taxonomic abundance profiles.
 
-There are currently two options for short-read preprocessing: `fastp` or `adapterremoval`.
+There are currently two options for short-read preprocessing: [`fastp`](https://github.com/OpenGene/fastp) or [`adapterremoval`](https://github.com/MikkelSchubert/adapterremoval).
 
 For adapter clipping, you can either rely on tool default adapter sequences, or supply your own adapters (`--shortread_qc_adapter1` and `--shortread_qc_adapter2`)
 By default, paired-end merging is not activated and paired-end profiling is performed where supported otherwise pairs will be independently profiled. If paired-end merging is activated you can also specify whether to include unmerged reads in the reads sent for profiling (`--shortread_qc_mergepairs` and `--shortread_qc_includeunmerged`).
 You can also turn off clipping and only perform paired-end merging, if requested. This can be useful when processing data downloaded from the ENA, SRA, or DDBJ (`--shortread_qc_skipadaptertrim`).
 Both tools support length filtering of reads and can be tuned with `--shortread_qc_minlength`. Performing length filtering can be useful to remove short (often low sequencing complexity) sequences that result in unspecific classification and therefore slow down runtime during profiling, with minimal gain.
 
-There is currently one option for long-read Oxford Nanopore processing: `porechop`.
+There is currently one option for long-read Oxford Nanopore processing: [`porechop`](https://github.com/rrwick/Porechop).
 
 For both short-read and long-read preprocessing, you can optionally save the resulting processed reads with `--save_preprocessed_reads`.
 
@@ -227,6 +227,8 @@ The tools offer different algorithms and parameters for removing low complexity
 
 You can optionally save the FASTQ output of the run merging with the `--save_complexityfiltered_reads`. If running with `fastp`, complexity filtering happens inclusively within the earlier shortread preprocessing step. Therefore there will not be an independent pipeline step for complexity filtering, and no independent FASTQ file (i.e. `--save_complexityfiltered_reads` will be ignored) - your complexity filtered reads will also be in the `fastp/` folder in the same file(s) as the preprocessed read.
 
+**We do not any read preprocessing or complexity filtering if you are using ONTs Guppy toolkit for basecalling and post-processing.**
+
 #### Host Removal
 
 Removal of possible-host reads from FASTQ files prior profiling can be activated with `--perform_shortread_hostremoval` or `--perform_longread_hostremoval`.
@@ -480,7 +482,7 @@ NXF_OPTS='-Xms1g -Xmx4g'
 Kraken2 allows the user to build custom databases. You can follow Kraken2 [tutorial](https://github.com/DerrickWood/kraken2/blob/master/docs/MANUAL.markdown#custom-databases).
 
 #### Centrifuge
-Centrifuge is similar to Kraken2 in that it enables to [build custom databases](https://ccb.jhu.edu/software/centrifuge/manual.shtml#custom-database). 
+Centrifuge allows the user to [build custom databases](https://ccb.jhu.edu/software/centrifuge/manual.shtml#custom-database).
 
 #### Kaiju
 It is possible to [create custom databases](https://github.com/bioinformatics-centre/kaiju#custom-database) with Kaiju.
@@ -495,12 +497,29 @@ malt-build -i path/to/fasta/files/*.{fna,fa} -s DNA -d index -t 8 -st 4 -a2t meg
 ```
 
 #### Bracken
+You can follow Bracken [tutorial](https://ccb.jhu.edu/software/bracken/index.shtml?t=manual) to build a custom database. Alternatively, you can use one of the indexes that can be found [here](https://benlangmead.github.io/aws-indexes/k2).
 
 #### KrakenUniq
+For KrakenUniq, we recommend using one of the available databases [here](https://benlangmead.github.io/aws-indexes/k2)
 
 #### DIAMOND
+To create a custom database for DIAMOND, the user should download and unzip the NCBI's taxonomy files. The `makedb` needs to be executed afterwards. A detailed description can be found [here](https://gensoft.pasteur.fr/docs/diamond/0.8.22/diamond_manual.pdf)
+
+```bash
+wget ftp://ftp.ncbi.nlm.nih.gov/pub/taxonomy/taxdmp.zip
+unzip taxdmp.zip
+
+## warning: large file!
+wget ftp://ftp.ncbi.nlm.nih.gov/pub/taxonomy/accession2taxid/prot.accession2taxid.FULL.gz
+
+## warning: takes a long time!
+cat ../raw/*.faa | diamond makedb -d testdb-diamond --taxonmap prot.accession2taxid.FULL.gz --taxonnodes nodes.dmp --taxonnames names.dmp
+
+rm *dmp *txt *gz *prt *zip
+```
 
 #### mOTUs
+A detailed description on how to download mOTUs database can be found [here](https://github.com/motu-tool/mOTUs)
 
 ## Troubleshooting and FAQs