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README.md

@@ -1,118 +1,45 @@
-# DRAM v2
+# DRAM2
+
+## Welcome to the wiki for Distilling and Refining Annotations of Metabolism 2 (DRAM2)!
+Here you will find give you basic instructions for running DRAM2, but for full documentation, please see the official DRAM2 webpage: [Read-the-docs](https://dramit.readthedocs.io/en/latest)
 
 <p align="center">
-  <img src="assets/images/DRAM2_large.png" width="600" height="600" alt="DRAM v2 logo">
+ <img src="assets/images/DRAM2_large.png" width="600" height="600" alt="DRAM v2 logo">
 </p>
 
-## ⚠️ DRAM v2 is currently under active development and usage is at your own risk. ⚠️
+## ⚠️ DRAM2 is currently under active development and usage is at your own risk. ⚠️
 
-DRAM v2 (Distilled and Refined Annotation of Metabolism Version 2) is a tool for annotating metagenomic and genomic assembled data (e.g. scaffolds or contigs) or called genes (e.g. nuclotide or amino acid format). DRAM annotates MAGs using [KEGG](https://www.kegg.jp/) (if provided by the user), [UniRef90](https://www.uniprot.org/), [PFAM](https://pfam.xfam.org/), [dbCAN](http://bcb.unl.edu/dbCAN2/), [RefSeq viral](https://www.ncbi.nlm.nih.gov/genome/viruses/), [VOGDB](http://vogdb.org/) and the [MEROPS](https://www.ebi.ac.uk/merops/) peptidase database as well as custom user databases.
+## DRAM2 Overview
+DRAM2 (Distilling and Refining Annotations of Metabolism, version 2) is a tool for annotating genomic and metagenomic assemblies (e.g., scaffolds or contigs) as well as predicted genes (nucleotide or amino acid sequences). It organizes genome annotations into metabolic functions across three levels of increasing interpretation: (1) **ANNOTATE**, (2) **SUMMARIZE**, and (3) **VISUALIZE**. This workflow enables the analysis of large numbers of microbial genomes or metagenomes, highlighting functional guilds and supporting inference of organismal metabolism across datasets.
 
-DRAM is run in four stages:
+During the **ANNOTATE** stage, DRAM2 identifies genes in input sequences and annotates them using multiple databases, including [KEGG](https://www.kegg.jp/) (if provided by the user), [UniRef90](https://www.uniprot.org/), [PFAM](https://pfam.xfam.org/), [dbCAN3](http://bcb.unl.edu/dbCAN2/), [RefSeq Viral](https://www.ncbi.nlm.nih.gov/genome/viruses/), [VOGDB](http://vogdb.org/), [MEROPS](https://www.ebi.ac.uk/merops/), and optional user-defined databases. A full list of available annotation databases can be found here: [WrightonLabCSU/dram pipeline parameters](https://dramit.readthedocs.io/en/latest/params_doc.html#pipeline-steps). ANNOTATE then integrates results across all databases, increasing annotation coverage and yielding ~25% more database hits than commonly used annotators such as DFAST, MetaERG, and Prokka.
 
-1. Gene Calling Prodogal - genes are called on user provided scaffolds or contigs
-2. Gene Annotation - genes are annotated with a set of user defined databases
-3. Distillation - annotations are curated into functional categories
-4. Product Generation - interactive visualizations of DRAM output are generated
+The **ANNOTATE** output contains all database hits for every gene in each genome, generating a comprehensive output of most annotation pipelines. DRAM2 extends beyond this by organizing (**SUMMARIZE**) and visualizing (**VISUALIZE**) annotations into ecosystem-relevant functional categories, enabling more interpretable comparisons across genomes and ecosystems.
 
-For more detail on DRAM and how DRAM v2 works please see our DRAM products:
+## Basic usage: 
+Below is an example of basic DRAM2 usage. This code is for annotating a directory of genomes, renaming them for downstream use, calling genes and annotating them using all available databases, performing quality control, summarizing and visualizing with particular ecosystems in mind and assigning genome-level traits to the organisms. The command is submitted on the command line and will run in the background. 
 
-- [DRAM version 1 publication](https://academic.oup.com/nar/article/48/16/8883/5884738)
-- [DRAM in KBase publication](https://pubmed.ncbi.nlm.nih.gov/36857575/)
-- [DRAM webinar](https://www.youtube.com/watch?v=-Ky2fz2vw2s)
 
-## Quick Links
+``` bash
+nextflow run WrightonLabCSU/DRAM --input_fasta [INPUT_FASTA] --outdir [OUTPUT_DIR] --rename --call --annotate --anno_dbs all --qc --summarize --sum_ecos 'eng_sys,ag' --visualize --traits -profile singularity -resume --slurm -bg
+```
+Please note that '--input_fasta [INPUT_FASTA]' should be a directory of genomes or MAGs in .fa or .fna format. It is also worth noting that all Nextflow options are specified with a single dash `-`, while all DRAM2-specific options are specified with a double dash `--`.  All available Nextflow options can be seen by running:
+
+`nextflow run -help`
 
+## Quick Links
 - [Docs](https://dramit.readthedocs.io/en/latest)
 - [Installation Guide](https://dramit.readthedocs.io/en/latest/installation.html)
 - [Usage Examples](https://dramit.readthedocs.io/en/latest/usage.html)
-- [Parameter API](<[#command-line-options](https://dramit.readthedocs.io/en/latest/params_doc.html)>)
-- [Rules API](<[#nextflow-tips-and-tricks](https://dramit.readthedocs.io/en/latest/rules_parser.html)>)
-
-## Example Usage
-
-DRAM apps Call, Annotate and Distill can all be run at once or alternatively, each app can be run individually. Here are some common usage examples:
-
-1. **Rename fasta headers based on input sample file names:**
-
-```bash
-nextflow run WrightonLabCSU/DRAM --rename --input_fasta <path/to/fasta/directory/>
-```
+- [Parameter API](https://dramit.readthedocs.io/en/latest/params_doc.html#pipeline-steps)
+- [Rules API](https://dramit.readthedocs.io/en/latest/rules_parser.html)
 
-2. **Call genes using input fastas (use --rename to rename FASTA headers):**
 
-```bash
-nextflow run WrightonLabCSU/DRAM --call --rename --input_fasta <path/to/fasta/directory/>
-```
-
-3. **Annotate called genes using input called genes and the KOFAM database:**
-
-```bash
-nextflow run WrightonLabCSU/DRAM --annotate --input_genes <path/to/called/genes/directory> --use_kofam
-```
-
-4. **Annotate called genes using input fasta files and the KOFAM database:**
-
-```bash
-nextflow run WrightonLabCSU/DRAM --annotate --input_fasta <path/to/called/genes/directory> --use_kofam
-```
-
-5. **Merge various existing annotations files together (Must be generated using DRAM):**
-
-```bash
-nextflow run WrightonLabCSU/DRAM --merge_annotations <path/to/directory/with/multiple/annotation/TSV/files>
-```
-
-6. **Distill using input annotations:**
-
-```bash
-nextflow run WrightonLabCSU/DRAM --distill_<topic|ecosystem|custom> --annotations <path/to/annotations.tsv>
-```
-
-7. **Complete workflow example:**
-
-```bash
-nextflow run -bg WrightonLabCSU/DRAM \
-  --input_fasta [DIRECTORY of fasta files] \
-  --outdir [OUTPUT] \
-  --rename --sum_ecos 'eng_sys,ag' \
-  -profile singularity,full_mode
-```
-
-## Nextflow Tips and Tricks
-
-The `-resume` option in Nextflow DSL2 allows you to efficiently manage and modify your workflow runs:
-
-- **Adding databases to an existing run:**
-  - Using `-resume` with your existing work directory lets you reuse called genes and existing annotations
-  - Example: If you initially used `--use_kofam --use_dbcan`, you can add `--use_kegg --use_uniref` and only the new annotations will be computed
-
-## Resource Management
-
-DRAM leverages Nextflow's horizontal scaling capabilities to distribute computational tasks across multiple computing resources. You can customize resource allocation through the `nextflow.config` file:
-
-- Modify "maxForks" parameters to control parallel execution
-- Configure CPU and memory requirements per process
-- Coming soon: "lite", "medium" and "heavy" modes for different computing environments
-
-## Configuration
-
-Every CLI option can be set in the `nextflow.config` file. For example:
-
-```nextflow
-params {
-    use_uniref = true
-    annotate = true
-}
-```
+## Other DRAM products from our research group:
+- [DRAM webinar](https://www.youtube.com/watch?v=-Ky2fz2vw2s)
+- [DRAM in KBase publication (2023)](https://pubmed.ncbi.nlm.nih.gov/36857575/)
 
-You can also use a custom config file:
-
-```bash
-nextflow run DRAM -c /path/to/custom_config.config
-```
 
 ## Citing DRAM
-
 If DRAM helps you in your research, please cite:
 [DRAM publication in Nucleic Acids Research (2020)](https://academic.oup.com/nar/article/48/16/8883/5884738)