Merge pull request #145 from qiyunzhu/update

Updated citation, description and installation guide.

README.md

@@ -4,9 +4,9 @@
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-**Woltka** (Web of Life Toolkit App), is a bioinformatics package for shotgun metagenome data analysis. It takes full advantage of, and is not limited by, the [WoL](https://biocore.github.io/wol/) reference phylogeny. It bridges first-pass sequence aligners with advanced analytical platforms (such as QIIME 2). Highlights of this program include:
+**Woltka** is a versatile program for determining the composition and functional capacity of microbiomes. It mainly works with shotgun metagenomic data. It bridges first-pass sequence aligners with advanced analytical platforms (such as QIIME 2). It takes full advantage of, and is not limited by, the [WoL](https://biocore.github.io/wol/) reference database. Highlights of this program include:
 
-- OGU: fine-grained community ecology.
+- [OGU](https://journals.asm.org/doi/10.1128/msystems.00167-22): fine-grained community ecology.
 - Tree-based, rank-free classification.
 - Combined taxonomic & functional analysis.
 
@@ -62,7 +62,7 @@ Woltka does NOT **analyze** profiles. We recommend using [QIIME 2](https://qiime
 
 ## Installation
 
-Requirement: [Python](https://www.python.org/) 3.6 or above, with Python package [biom-format](http://biom-format.org/) installed.
+Requirement: [Python](https://www.python.org/) 3.6 or above.
 
 ```bash
 pip install woltka
@@ -133,11 +133,11 @@ One can also combine taxonomic and functional profilings in a **stratification**
 
 ## Citation
 
-The first manuscript describing Woltka has been preprinted at:
+The first paper describing Woltka was published at:
 
-- Zhu Q, Huang S, Gonzalez A, McGrath I, McDonald D, Haiminen N, et al. [OGUs enable effective, phylogeny-aware analysis of even shallow metagenome community structures.](https://www.biorxiv.org/content/10.1101/2021.04.04.438427v1) _bioRxiv_. 2021. doi: https://doi.org/10.1101/2021.04.04.438427.
+- Zhu Q, Huang S, Gonzalez A, McGrath I, McDonald M, Haiminen N, Armstrong G, et al. [Phylogeny-aware analysis of metagenome community ecology based on matched reference genomes while bypassing taxonomy.](https://journals.asm.org/doi/10.1128/msystems.00167-22) _mSystems_. 2022. e00167-22.
 
-Note: This manuscript focuses on the [OGU analysis](doc/ogu.md). Although it does not discuss other functions of Woltka, it is so far the only citable article if you use Woltka in your studies.
+Note: This paper focuses on the [OGU analysis](doc/ogu.md). Although it does not discuss other functions of Woltka, it is so far the only citable paper if you use Woltka in your studies.
 
 
 ## Contact

doc/install.md

@@ -13,7 +13,6 @@ We recommend [Conda](https://docs.conda.io/en/latest/) for managing Python versi
 ```bash
 conda create -n woltka python=3
 conda activate woltka
-conda install -c conda-forge cython biom-format
 ```
 
 If you already have a [QIIME 2](https://qiime2.org/) environment, these steps can be omitted as the dependencies are already included. See [details](../woltka/q2).

doc/ogu.md

@@ -2,11 +2,12 @@
 
 The notion of “**OGU**” (operational genomic unit) is the minimal unit for community ecology studies based on shotgun metagenome or other forms of whole-genome microbiome data. OGUs are simply the reference genomes to which input sequences are aligned. There is no need to assign taxonomy to them. This is in constrast to conventional practices, in which analyses are based on taxonomic units such as genera or species. Therefore, OGU is analogous to ASV in 16S rRNA studies.
 
-The advantage of using OGUs includes 1) highest-possible resolution, 2) independent from taxonomy which is coarse and error-prone as a classification system. 3) allowing for phylogeny-based analysis such as Faith’s PD and UniFrac. The last part is enhanced by the “Web of Life” ([WoL](https://biocore.github.io/wol/)) reference phylogeny.
+The advantage of using OGUs includes 1) highest-possible resolution, 2) independent from taxonomy which is coarse and error-prone as a classification system. 3) allowing for phylogeny-based analysis such as Faith’s PD and UniFrac. The last part is enhanced by the "Web of Life" ([WoL](https://biocore.github.io/wol/)) reference phylogeny.
 
-Our manuscript introducing the OGU analysis has been preprinted at:
+The OGU analysis was explained, benchmarked and discussed in:
+
+- Zhu Q, Huang S, Gonzalez A, McGrath I, McDonald M, Haiminen N, Armstrong G, et al. [Phylogeny-aware analysis of metagenome community ecology based on matched reference genomes while bypassing taxonomy.](https://journals.asm.org/doi/10.1128/msystems.00167-22) _mSystems_. 2022. e00167-22.
 
-- Zhu Q, Huang S, Gonzalez A, McGrath I, McDonald D, Haiminen N, et al. [OGUs enable effective, phylogeny-aware analysis of even shallow metagenome community structures.](https://www.biorxiv.org/content/10.1101/2021.04.04.438427v1) _bioRxiv_. 2021. doi: https://doi.org/10.1101/2021.04.04.438427.
 
 
 ## Contents

doc/wol.md

@@ -70,7 +70,7 @@ fastp -l 100 -i forward.fastq -I reverse.fastq -o forward_trimmed.fastq -O rever
 
 ## The OGU analysis
 
-**OGU** (operational genomic unit) ([Zhu et al., 2021](https://www.biorxiv.org/content/10.1101/2021.04.04.438427v1)) is a notion we proposed to define the minimum unit of microbiome composition allowed by shotgun metagenomic data. OGUs are reference genomes to which any input sequences have matches. This maximizes the resolution of microbiome composition, and allows for phylogeny-aware analyses using the WoL reference phylogeny. See [details](ogu.md).
+**OGU** (operational genomic unit) ([Zhu et al., 2022](https://journals.asm.org/doi/10.1128/msystems.00167-22)) is a notion we proposed to define the minimum unit of microbiome composition allowed by shotgun metagenomic data. OGUs are reference genomes to which any input sequences have matches. This maximizes the resolution of microbiome composition, and allows for phylogeny-aware analyses using the WoL reference phylogeny. See [details](ogu.md).
 
 In Woltka, an OGU analysis is simply a classification process without a classification system. In such case, the output features will just be the subjects in the alignment file, namely reference genomes.