I think the most common practice is to first check the data for quality, e.g. fastqc (http://www.bioinformatics.babraham.ac.uk/projects/fastqc/). Since it runs on java, it should work on mac.

It is quite vague what differential expression means in your question (genes, transcripts or something else?). There are popular tools for computing differential expressed genes, they all have built-in normalization techniques, e.g. DESeq and edgeR. These are R packages, so you probably have to install the mac version of R before using them. They are pretty straight forward to use if you read the manuals.

Hi,

Checking the quality of your data with fastQC is the first step. Afterwards, you could use STAR for the NGS read mapping, featureCounts for calculating the raw counts and DeSeq2 for the differential gene expression analysis. The details are up to your specific question. Mapping and counting of sequencing reads requires an annotated reference genome sequence. Is it available for your species?

Best,

Boas

Hi, you have a lot of different choices regarding analysis of NGS data. From your question, I guess you are interested in RNA-seq or gene expression data. In this cas, you can use fastQC for a first quality check of your raw sequences, then choose among the many sequence aligners (STAR, TopHat2 / bowtie2, Hisat...). Afterwards it depends if you're interested in just differential gene expression or in alternative splicing / differential RNA isoforms use. In the first case featureCount or HTseq-count (script in python language) followed by DESeq2 analysis (R package) are the most classical tools, in the second case you can use the Cufflinks / Cuffdiff software suit. Most of all these tools are also available online through GALAXY (usegalaxy.org), if you don't want to bother with command lines.

Good luck and welcome in NGS bio-informatics!

Hi all,

Thanks you all very much for your detailed replies. I'll check it out. Luckily I have R language installed and can approach to python through terminal.

Here's a question (maybe a little stupid), among these tools mentioned above, do we start with the zip file given by the sequencing company or should we ask the company to give us csv or txt file... :-)

Thanks~

Hi again,

You should get '.fastq' files if Illumina technology was used. These files might be compressed as '.gz' or '.gzip'. You do not need to uncompress the files. Most tools e.g. fastQC and STAR can work with compressed files. It saves a lot of disk space.