fix hierarchy

topics/proteomics/tutorials/metaproteomics/tutorial.md

@@ -25,9 +25,6 @@ subtopic: multi-omics
 tags: [microbiome]
 ---
 
-# Introduction
-
-
 In this metaproteomics tutorial we will identify expressed proteins from a complex bacterial community sample.
 For this MS/MS data will be matched to peptide sequences provided through a FASTA file.
 
@@ -117,7 +114,7 @@ will be used to match MS/MS to peptide sequences via a sequence database search.
 For this, the sequence database-searching program called [SearchGUI](https://compomics.github.io/projects/searchgui.html) will be used.
 The created dataset collection of the three *MGF files* in the history is used as the MS/MS input.
 
-#### SearchGUI
+### SearchGUI
 
 > <hands-on-title>SearchGUI</hands-on-title>
 >
@@ -183,7 +180,7 @@ SearchGUI archive file) that will serve as an input for the next section, Peptid
 >
 {: .comment}
 
-#### PeptideShaker
+### PeptideShaker
 
 [PeptideShaker](https://compomics.github.io/projects/peptide-shaker.html) is a post-processing software tool that
 processes data from the SearchGUI software tool. It serves to organize the Peptide-Spectral
@@ -262,7 +259,7 @@ proteins and provides a fast matching algorithm for peptides.
 > or operated on within Galaxy.
 {: .comment}
 
-#### Recieving the list of peptides: Query Tabular
+### Recieving the list of peptides: Query Tabular
 
 In order to use *Unipept*, a list containing the peptide sequences has to be generated.
 The tool **Query Tabular** can load tabular data (the PSM report in this case) into a SQLite data base.
@@ -364,7 +361,7 @@ Therefore we can search the database for the peptides and count the occurrence w
 {: .hands_on}
 
 
-#### Retrieve taxonomy for peptides: Unipept
+### Retrieve taxonomy for peptides: Unipept
 
 The generated list of peptides can now be used to search via *Unipept*.
 We do a taxonomy analysis using the UniPept pept2lca function to return the taxonomic lowest common ancestor for each peptide:
@@ -496,7 +493,7 @@ This allows to get an insight of the **biological process**, the **molecular fun
 >
 {: .comment}
 
-#### Data upload
+### Data upload
 
 For this tutorial, a tabular file containing the relevant GO terms has been created. It contains the GO aspect, the ID and the name.
 It is available at Zenodo: [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.839701.svg)](https://doi.org/10.5281/zenodo.839701).
@@ -533,7 +530,7 @@ It is available at Zenodo: [![DOI](https://zenodo.org/badge/DOI/10.5281/zenodo.8
 >
 {: .details}
 
-#### Retrieve GO IDs for peptides: Unipept
+### Retrieve GO IDs for peptides: Unipept
 
 The **UniPept** application `pept2prot` can be used to return the list of proteins containing each peptide.
 The option `retrieve extra information` option is set to `yes` so that we retrieve Gene Ontology assignments (`go_references`)
@@ -559,7 +556,7 @@ for each protein.
 {: .hands_on}
 
 
-#### Combine all information to quantify the GO results
+### Combine all information to quantify the GO results
 
 As a final step we will use **Query Tabular** in a more sophisticated way to combine all information to quantify the GO analysis. The three used file and the extracted information are: