I'm planning to write a bioinformatics pipeline in R. (...)

what should I avoid in R ?

don't reinvent the wheel: make or other tools like snakemake are the workflow managers you need: How To Organize A Pipeline Of Small Scripts Together?

It usually makes more sense to incorporate an R script into a pipeline rather than writing the pipeline itself in R.

The best R pipeline example I have seen is the Nature Protocols paper -

Count-based differential expression analysis of RNA sequencing data using R and Bioconductor

If you don't have access to the journal, here is pre-publication version.

R and Bioconductor related lilbaries are captured in command

> sessionInfo()

The versions of system software packages are captured:
> system("bowtie2 --version | grep align", intern=TRUE)

[1] "/usr/local/software/bowtie2-2.1.0/bowtie2-align version 2.1.0"

It is a deep learning curve to learn R well enough to write the whole bioinformatics pipepine in R. Good luck :)

I do a lot of scripting in R, and with ggplot2 and bioconductor; there is so much one can achieve. Pipelining was surely a issue, so we built a tool to do just that (http://docs.flowr.space). One starts with a bunch of system commands, wraps them into a tab-delim text file. When done flowr can submit to a local server (parallel using mclapply), and clusters like LSF, Torque, SLURM and MOAB etc...

Usage:
flowr function [arguments]
   status Detailed status of a flow(s).
   rerun rerun a previously failed flow kill
   Kill the flow, upon providing working directory
   fetch_pipes Checking what modules and pipelines are available;

Please use 'flowr -h function' to obtain further information about the usage of a specific function.

Certainly biased (being a developer) but one may find it much easier to create a tsv file, than learning new syntax.

Second issue I faced was, say I have a R function which does a lot of things and now I wanted to call it from the terminal. R does not have a nice standard argument parse like python/perl. Now we have a package funr, where the first argument is the function you want to call, and rest are its arguments. One can call any R function of any installed package (or sourced script).

funr rnorm n=10
    -1.244571 1.378112 0.02189023 -0.3723951 0.282709 -0.22854 -0.8476185 0.3222024 0.08937781 -0.4985827

Hope you find it useful. Would be curious if it works out.