In cparsania/FungiExpresZ: FungiExpresZ: Fungal gene expression data analysis and visualizations

```{=html}

      

```r
knitr::opts_chunk$set(echo = TRUE)
app_name <-  "FungiExpresZ"
#library(tidyverse)
library(knitr)
library(kableExtra)

About this page

This page is all about notifying users regarding new features, bug fixing, any other important changes or announcements made on r app_name over the time.

r lubridate::date(x = "2023/12/01")

Release version 2.2.0

• FungiExpresZ annotations have been upgraded to FungiDB v66 from v64.

• Number of species are increased to 275 from 247.

• Bug fix and performance improvement.

r lubridate::date(x = "2023/07/21")

Release version 2.1.0

• FungiExpresZ annotations have been upgraded to FungiDB v64 from v42.

• Number of species are increased to 247 from 122.

• Bug fix and performance improvement.

r lubridate::date(x = "2023/05/26")

Release version 2.0.0

In this release FungiExpresZ has been upgraded to R 4.2.2

r lubridate::date(x = "2023/04/04")

New SRA data

From the species Aspergillus terreus.

r lubridate::date(x = "2022/10/21")

Release v1.3

It includes..

• About 3,000 new data-sets from 10 new fungal species.

• Line plot random disappearance is fixed.

• Improved documentation.

• Bug fixes and performance improvement.

r lubridate::date(x = "2022/10/10")

New SRA data

We have now added more than 3,000 SRA samples from 10 new fungal species. In total, FungiExpresZ contains \~16,000 SRA data data from 18 different fungal species. Full list of the available species and corresponding datasets can be found under the tab Downloads -> Gene expression data.

r lubridate::date(x = "2022/01/30")

Introducing Step-by-step guide page.

This is a user manual describing all options given in the r app_name.

r lubridate::date(x = "2020/02/25")

Introducing citation page.

Under the page Citations, you can see publications citing FungiExpresZ.

r lubridate::date(x = "2019/11/7")

GO analysis updates

Three new options are added in GO analysis.

1. Background Genes to GO mapping

It allows user to select type of background data (Genes to GO mapping) to use for GO enrichment analysis. It has two options.

• Parent + Offsprings : For a given GO term A, all the genes from A and A's offspring GO terms will be considered as a part of term A.
• Parent : For a given GO term A, all the genes from A will be considered as a part of term A.

2. # of minimum genes in a GO term

Using this option user can restrict the GO enrichment output. Only those GO terms will be displayed, which has minimum number of genes more than cutoff value.

3. # of maximum genes in a GO term

Using this option user can restrict the GO enrichment output. Only those GO terms will be displayed, which has maximum number of genes less than cutoff value.

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r lubridate::date(x = "2019/11/1")

Overview page introduced

Under the tab About --> Overview page is created. As name suggests, it gives an overview and functionality of the r app_name. In addition, we provided example plots generated from cartoon data. Users can take ideas from example plots and replicate them for their own data.

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r lubridate::date(x = "2019/10/14")

New logo introduced

r app_name has its identity now. Introducing new logo 🎉🎉🎉🎉

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r lubridate::date(x = "2019/10/10")

Available as a docker image

r app_name is now available as a docker image and can be run as a container on any local computer where docker hub is installed. Follow instructions given on Github{target="_blank"} to install and run locally.

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r lubridate::date(x = "2019/10/08")

Available as an R package (v0.0.1)

r app_name can be installed as an R package and run on local computer. For local installation, please follow instruction on Github{target="_blank"}

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r lubridate::date(x = "2019/09/23")

New SRA data added for Aspergillus fumigatus and Aspergillus niger

Number of samples increased to 242 from 133 and 253 from 28 for Aspergillus fumigatus and Aspergillus niger respectively.

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r lubridate::date(x = "2019/09/18")

Download data

• r app_name allows user to download gene ontology data and gene expression matrix in.txt file format. Data can be downloaded under the tab Downloads.

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r lubridate::date(x = "2019/09/16")

Improved line plot

• Performance of line plot is improved.
• Along with gene clusters, individual genes can also be plotted.
• Color and facet by gene groups can be done.
• Line size and transparency can be changed.

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r lubridate::date(x = "2019/09/14")

Video tutorials

• r app_name tutorial videos have been given under tab Tutorial. User can also watch videos on YouTube channel{target="_blank"}.

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r lubridate::date(x = "2019/09/09")

Display active groups

• User can see now active gene groups and active sample groups any time while accessing the app. Groups can be seen under the section of side panel View active groups.

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r lubridate::date(x = "2019/08/30")

New GO visualizations: UpSet plot and Bar plot

• Two more GO visualizations added : 1) UpSet plot and 2) Bar plot. With addition of these two GO plots, r app_name has now total 6 different GO visualizations. GO visualizations can be done for the genes selected from scatter plot or gene clusters selected from line plot and heatmap.

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r lubridate::date(x = "2019/08/27")

Use NCBI BioProject as sample groups

• While using the SRA data given in the r app_name, user can use NCBI BioProjects as sample groups. Using NCBI BioProjects as sample groups allow user to compare between SRA samples of multiple studies. To use NCBI BioProjects as sample groups follow this Assign groups --> Samples --> Group by BioProjects (NCBI).

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r lubridate::date(x = "2019/08/09")

Access SRA sample information for heatmap column clusters

• Most obvious questions to ask once the heatmap created are 1) what are the samples under column clusters and 2) what are the genes under the row clusters. r app_name has already provided GO analysis feature for the row clusters. Now, the new feature allow user to get sample information for a specified column cluster. For a selected column cluster r app_name displays below information.

  knitr::kable(tibble::tibble("Heatmap column label", "NCBI Bio project ID", "Library Name", "Strain", "Genotype", "Study title", "Study abstract"), col.names = NULL) %>% 
  kableExtra::kable_styling(bootstrap_options = "striped", full_width = T, position = "center")

Visualize heatmap column cluster sample information in the word cloud plot

• Heatmap is the powerful way to visualize the gene expression data. In general, columns represents different samples and rows represents genes. Implying various clustering methods on heatmap rows and column can identify clusters of similar expression profiles. For ease of understanding samples under given column cluster, r app_name provides word cloud visualization. For a given column cluster, it collects unique set of study abstract and perform word enrichment using text mining. The enriched words are displayed in form of word cloud plot. Word cloud feature can be accessed once the heatmap created using SRA samples.

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r lubridate::date(x = "2019/08/01")

Newz and update page introduced

• First time Newz and Update page introduced. Form now onward, updates / new feature / bug fixing etc. will be reported on this page.

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cparsania/FungiExpresZ documentation built on March 15, 2024, 5:48 p.m.