What topic (e.g. R package) will you showcase?
Mostly about the package 'xlsx'. I will be showing a way of integrating results from multiple genomic analyses or pipelines and produce a multi-tab excel sheet that stores all the data tables and figures in a single excel file (or loop the pipeline to generate multiple excel files)
Why do you think it's worthwhile learning about this topic/package?
It is common that for at the end stage of genomic studies, one could arrive at a point with 50 genes of interest and ask...what do we know about these genes? what were the results of SNV or expresssion or pathway analyses I performed for each of these genes?
My goal is to generate a single excel file for each gene, containing all the analyses results about this gene, including data tables, figures, literature text-mining etc. as an integrated report.
It's important to state the motivation so it's clear to readers why they should read further.
What dataset will you use?
Preferably, pick a dataset that is relatively small.
If the dataset is large, you can subset it to make it smaller (e.g. subset on chromosomes 20-22).
Try to leverage datasets that are used elsewhere in this set of tutorials.
It would be nice if there was a permalink for downloading the dataset. If a custom dataset is created (e.g. subsetting an existing large dataset), it would be great if the custom version was hosted somewhere (e.g. FigShare) so you can provide a permalink.
I will be using the results generated by all the analyses we are doing. Or a list of genes significant from certain analyses we showcased.
What software dependencies need to be installed?
R packages are usually easy to install, so it's okay to install a few R packages.
Other command-line tools might be harder to set up on certain systems (e.g. Windows), so try to limit the number of external tool dependencies.
Mostly the package '.xlsx', currently, there is not a very useful tutorial on this package on the web.
The package 'animation' is sometimes used when some R processes automatically store a figure in .PDF format, which requires to be converted to .PNG to be imported into an excel sheet.
What will you cover in your tutorial?
This roughly corresponds to an outline of what you will accomplish in your tutorial using the dataset you picked.
How to create a workbook, worksheets, how to export results (data tables, figures, texts) onto the .xlsx.
What topic (e.g. R package) will you showcase?
Mostly about the package 'xlsx'. I will be showing a way of integrating results from multiple genomic analyses or pipelines and produce a multi-tab excel sheet that stores all the data tables and figures in a single excel file (or loop the pipeline to generate multiple excel files)
Why do you think it's worthwhile learning about this topic/package?
It is common that for at the end stage of genomic studies, one could arrive at a point with 50 genes of interest and ask...what do we know about these genes? what were the results of SNV or expresssion or pathway analyses I performed for each of these genes?
My goal is to generate a single excel file for each gene, containing all the analyses results about this gene, including data tables, figures, literature text-mining etc. as an integrated report.
It's important to state the motivation so it's clear to readers why they should read further.
What dataset will you use?
Preferably, pick a dataset that is relatively small.
If the dataset is large, you can subset it to make it smaller (e.g. subset on chromosomes 20-22).
Try to leverage datasets that are used elsewhere in this set of tutorials.
It would be nice if there was a permalink for downloading the dataset. If a custom dataset is created (e.g. subsetting an existing large dataset), it would be great if the custom version was hosted somewhere (e.g. FigShare) so you can provide a permalink.
I will be using the results generated by all the analyses we are doing. Or a list of genes significant from certain analyses we showcased.
What software dependencies need to be installed?
R packages are usually easy to install, so it's okay to install a few R packages.
Other command-line tools might be harder to set up on certain systems (e.g. Windows), so try to limit the number of external tool dependencies.
Mostly the package '.xlsx', currently, there is not a very useful tutorial on this package on the web.
The package 'animation' is sometimes used when some R processes automatically store a figure in .PDF format, which requires to be converted to .PNG to be imported into an excel sheet.
What will you cover in your tutorial?
This roughly corresponds to an outline of what you will accomplish in your tutorial using the dataset you picked.
How to create a workbook, worksheets, how to export results (data tables, figures, texts) onto the .xlsx.