From f22cf0c921a2f1eb78ed807111966f3e2002307c Mon Sep 17 00:00:00 2001
From: Sofia Stamouli <91951607+sofstam@users.noreply.github.com>
Date: Tue, 11 Oct 2022 16:41:44 +0200
Subject: [PATCH] Update usage.md

---
 docs/usage.md | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

diff --git a/docs/usage.md b/docs/usage.md
index 8b8b588..aec51dc 100644
--- a/docs/usage.md
+++ b/docs/usage.md
@@ -145,6 +145,7 @@ Expected (uncompressed) database files for each tool are as follows:
   with same release version of the mOTUs tools. The database for same version tools
   can be thus reused for multiple runs. Users can download the database once using the script above and
   specify the path the database to the TSV table provided to `--databases`.
+- **KrakenUniq**
 
 ## Running the pipeline
 
@@ -199,7 +200,9 @@ Complexity filtering is primarily a run-time optimisation step. It is not necess
 
 There are currently three options for short-read complexity filtering: [`bbduk`](https://jgi.doe.gov/data-and-tools/software-tools/bbtools/bb-tools-user-guide/bbduk-guide/), [`prinseq++`](https://github.com/Adrian-Cantu/PRINSEQ-plus-plus), and [`fastp`](https://github.com/OpenGene/fastp#low-complexity-filter).
 
-The tools offer different algorithms and parameters for removing low complexity reads. We therefore recommend reviewing the pipeline's [parameter documentation](https://nf-co.re/taxprofiler/parameters) and the documentation of the tools (see links above) to decide on optimal methods and parameters for your dataset.
+There is one option for long-read quality filtering:  [`Filtlong`](https://github.com/rrwick/Filtlong)
+
+The tools offer different algorithms and parameters for removing low complexity reads and quality filtering. We therefore recommend reviewing the pipeline's [parameter documentation](https://nf-co.re/taxprofiler/parameters) and the documentation of the tools (see links above) to decide on optimal methods and parameters for your dataset.
 
 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.