On date unavailable, commented:

None

On 2015 Sep 23, Guangchuang Yu commented:

• 1. The so called Linux-like should be Unix-like.
• 2. you should also present runseq2pathway runnable example.
• 3. it seems you are not familiar with R

tmp <- sessionInfo() mySession <- ifelse(length(grep("Windows",tmp))==0, "L","W")

I recommend you use Sys.info() to extract platform information.

if (mySession=="W") sink(paste(tempdir(),"\",name,sep="")) else sink(file.path(tempdir(),name,fsep = .Platform$file.sep))

actually '/' works fine with Windows and Unix-like system in R. Why not just use:

name = tempfile()

and write your python script to that file?

On 2015 Sep 20, Xinan Holly Yang commented:

Thank you for pointing out. We have fixed the bug in the seq2pathway version >=1.1.6 as described below:

1) The new seq2pathway package runs on both Windows and Linux-like systems.

2) We activated a demon code:

data(ChipseqPeakdemo)

runseq2gene(inputfile=ChipseqPeakdemo)

3) We replaced the absolute path with Sys.which("python").

The significance of the package for the end-users could be:

1) It provides a detailed map and a flexible search of the human and mouse genome. Compared to other tools using the UCSC genome, we processed the newest GENCODE data thus can provide more information for the non-coding regions. Importantly, the runseq2gene() function is designed to find more target gene candidates for a given genomic locus using a customized search radius, which will help users to study trans-regulation. In fact, we have applied the method for the biological knowledge discovery (PLoS Genet. 2014 Oct; 10(10): e1004604, PLoS Genet. 2014 Oct; 10(10): e1004604.http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4214600/).

2) The se2pathway package implements a unique gene2pathway algorithm termed FAIME (PLoS Comput Biol. 2014 May;10(5):e1003609. http://www.ncbi.nlm.nih.gov/pubmed/22291585) and other three widely-used gene-set analysis (GSA) approaches. It also provides a way to include user-defined gene-sets, which is an adding to the current GSA tools and is important for the discovery of function. Unlike conventional GSA approaches, the package also calculates a corrected background for a more accurate Fisher's exact test (We have introduced the algorithm at BMC Medical Genomics 2015, 8(Suppl 2):S6 http://www.biomedcentral.com/1755-8794/8/S2/S6).

3) Furthermore, the package provides end-users a one-command option to find enriched pathways from 'omic' data.

Looking forwards to more users and comments and we will further improve the package.

-Holly

On 2015 Aug 21, Guangchuang Yu commented:

not runnable, see the post.

On 2015 Aug 21, Guangchuang Yu commented:

not runnable, see the post.

On 2015 Sep 20, Xinan Holly Yang commented:

Thank you for pointing out. We have fixed the bug in the seq2pathway version >=1.1.6 as described below:

1) The new seq2pathway package runs on both Windows and Linux-like systems.

2) We activated a demon code:

data(ChipseqPeakdemo)

runseq2gene(inputfile=ChipseqPeakdemo)

3) We replaced the absolute path with Sys.which("python").

The significance of the package for the end-users could be:

1) It provides a detailed map and a flexible search of the human and mouse genome. Compared to other tools using the UCSC genome, we processed the newest GENCODE data thus can provide more information for the non-coding regions. Importantly, the runseq2gene() function is designed to find more target gene candidates for a given genomic locus using a customized search radius, which will help users to study trans-regulation. In fact, we have applied the method for the biological knowledge discovery (PLoS Genet. 2014 Oct; 10(10): e1004604, PLoS Genet. 2014 Oct; 10(10): e1004604.http://www.ncbi.nlm.nih.gov/pmc/articles/PMC4214600/).

2) The se2pathway package implements a unique gene2pathway algorithm termed FAIME (PLoS Comput Biol. 2014 May;10(5):e1003609. http://www.ncbi.nlm.nih.gov/pubmed/22291585) and other three widely-used gene-set analysis (GSA) approaches. It also provides a way to include user-defined gene-sets, which is an adding to the current GSA tools and is important for the discovery of function. Unlike conventional GSA approaches, the package also calculates a corrected background for a more accurate Fisher's exact test (We have introduced the algorithm at BMC Medical Genomics 2015, 8(Suppl 2):S6 http://www.biomedcentral.com/1755-8794/8/S2/S6).

3) Furthermore, the package provides end-users a one-command option to find enriched pathways from 'omic' data.

Looking forwards to more users and comments and we will further improve the package.

-Holly