In general linux is the platform of choice for bioinformatics. Other bioinformatics requirements are computational power and vast storage options. The files are rather large.
If you are unfamiliar with Linux or lack high-end computers, several cloud solutions exist that enables you to perform basic and advanced stuff on ordinary off-the shelves PCs. One such tool is Galaxy (https://usegalaxy.org/). But multiple others exists depending upon your NGS platform and field of work.
How familiar are you with R & BioConductor? You really need to be comfortable working with R packages as many tools are developed as R packages.
Some basic scripting knowledge is useful - PERL, Python, shell scripts. Not necessarily anything complicated, but being able to deftly parse and convert files, as well as automate simply connections between one analytical tool and the next can make life much easier and get things done quickly.
Also, do you have access to any commercial packages where you are now? A number of large commercial packages exist as well that are excellent - JMP Genomics from SAS, MatLab has NGS components, Partek, and others all have some very good tools, if you have access to them (they do tend to be expensive, so hopefully your center has a site license for some).
What kind of NGS data and analyses are you working with? RNA-seq, paired-end, ChipSeq, transcriptome assembly, targeted deep sequencing, differential gene expression, SNP-finding, transcriptional regulation studies...?? NGS covers a wide range of data types and applications, and the tools vary even more so as there are multiple software packages to handle any one of them.
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