Updated workflow diagrams within platform specific folders to architecture diagrams

Author: aolveraNIH

AWS/README.md

@@ -3,7 +3,7 @@
 + [Overview](#overview)
 + [Learning goals](#learning-goals)
 + [Biological Problem](#biological-problem)
-+ [Workflow Diagrams](#workflow-diagrams)
++ [Architecture Diagram](#architecture-diagram)
 + [Data](#data)
 + [Troubleshooting](#troubleshooting)
 + [Funding](#funding)
@@ -28,12 +28,9 @@ Transcriptome assembly is the broad term used to describe the process of estimat
 
 Once a new transcriptome is generated, assessed, and refined, it must be annotated with putative functional assignments to be of use in subsequent functional studies.  Functional annotation is accomplished through a combination of assignment of homology-based and ab initio methods. The most well-established homology-based processes are the combination of protein-coding sequence prediction followed by protein sequence alignment to databases of known proteins, especially those from human or common model organisms. Ab initio methods use computational models of various features (e.g., known protein domains, signal peptides, or peptide modification sites) to characterize either the transcript or its predicted protein product. This training module will cover multiple approaches to the annotation of assembled transcriptomes.
 
-## **Workflow Diagrams**
+## **Architecture Diagram**
 
-![transpi workflow](../images/transpi_workflow.png)
- 
-**Figure 3:** Nextflow workflow diagram. (Rivera 2021).  
-Image Source: https://github.com/PalMuc/TransPi/blob/master/README.md
+![nf-core workflow](../images/Transcriptome_Assembly_Maine_AWS.svg)
 
 ## **Data** 
 The test dataset used in the majority of this module is a downsampled version of a dataset that can be obtained in its complete form from the SRA database (Bioproject [**PRJNA318296**](https://www.ncbi.nlm.nih.gov/bioproject/PRJNA318296), GEO Accession [**GSE80221**](https://www.ncbi.nlm.nih.gov/geo/query/acc.cgi?acc=GSE80221)). The data was originally generated by **Hartig et al., 2016**. We downsampled the data files in order to streamline the performance of the tutorials and stored them in an s3 bucket. The sub-sampled data, in individual sample files as well as a concatenated version of these files are available in our s3 bucket at `s3://nigms-sandbox/nosi-inbremaine-storage/resources/seq2`.

GoogleCloud/README.md

@@ -3,7 +3,7 @@
 + [Overview](#overview)
 + [Learning goals](#learning-goals)
 + [Biological Problem](#biological-problem)
-+ [Workflow Diagrams](#workflow-diagrams)
++ [Architecture Diagram](#architecture-diagram)
 + [Data](#data)
 + [Troubleshooting](#troubleshooting)
 + [Funding](#funding)
@@ -28,12 +28,10 @@ Transcriptome assembly is the broad term used to describe the process of estimat
 
 Once a new transcriptome is generated, assessed, and refined, it must be annotated with putative functional assignments to be of use in subsequent functional studies.  Functional annotation is accomplished through a combination of assignment of homology-based and ab initio methods. The most well-established homology-based processes are the combination of protein-coding sequence prediction followed by protein sequence alignment to databases of known proteins, especially those from human or common model organisms. Ab initio methods use computational models of various features (e.g., known protein domains, signal peptides, or peptide modification sites) to characterize either the transcript or its predicted protein product. This training module will cover multiple approaches to the annotation of assembled transcriptomes.
 
-## **Workflow Diagrams**
+## **Architecture Diagram**
+
+![nf-core workflow](images/Transcriptome_Assembly_Maine_GCP.svg)
 
-![transpi workflow](images/transpi_workflow.png)
- 
-**Figure 3:** Nextflow workflow diagram. (Rivera 2021).  
-Image Source: https://github.com/PalMuc/TransPi/blob/master/README.md
 
 Explanation of which notebooks execute which processes:
 

README.md

@@ -28,7 +28,7 @@ Transcriptome assembly is the broad term used to describe the process of estimat
 
 Once a new transcriptome is generated, assessed, and refined, it must be annotated with putative functional assignments to be of use in subsequent functional studies.  Functional annotation is accomplished through a combination of assignment of homology-based and ab initio methods. The most well-established homology-based processes are the combination of protein-coding sequence prediction followed by protein sequence alignment to databases of known proteins, especially those from human or common model organisms. Ab initio methods use computational models of various features (e.g., known protein domains, signal peptides, or peptide modification sites) to characterize either the transcript or its predicted protein product. This training module will cover multiple approaches to the annotation of assembled transcriptomes.
 
-## **Workflow Diagrams**
+## **Workflow Diagram**
 
 ![nf-core denovotranscript workflow](images/denovotranscript_metro_map.svg)