Rna Seq Data Analysis

Question

[sara]

Hi all!!!

I am new to analysis the RNA-seq data.

As far now i used bowtie for indexing the reference genome, picard to find mate-inner-distance, tophat for aligning our reads to the reference genome, cufflink to get GTF file of transcript, cuffmerge to merge the transcript file of both diseased and normal, And then i did cuffdiff to get differention expression data.

Now am having

    bias_params.info, cds.count_tracking, cds.diff, cds.fpkm_tracking, cds.read_group_tracking, cds_exp.diff, gene_exp.diff, genes.count_tracking, genes.fpkm_tracking, genes.read_group_tracking, isoform_exp.diff, isoforms.count_tracking, isoforms.fpkm_tracking, isoforms.read_group_tracking, promoters.diff, read_groups.info, splicing.diff, tss_group_exp.diff, tss_groups.count_tracking, tss_groups.fpkm_tracking, tss_groups.read_group_tracking, var_model.info.

These are the files i got in after running cuffdiff. Can anyone help me on hoe to proceed further?

Answer 1

[ThePresident]

The file called "gene_exp.diff" will contain everything you need for differential expression (including statistical parameters). You might begin with that file to asses you DE genes.

edit: you can use "genes.fpkm_tracking" to get your FPKM values which can be useful to compare genes expression within a single library.

Answer 2

[Sudeep]

Before going in any direction, I would recommend to go through some of the previous Biostar threads like Rna-Seq Review Papers, Survey: Rna-Seq Analysis For Differential Gene/Transcript Expression [Updated With Results] and Rna-Seq Data Analysis & Good Review/Research Article On Same. The links in those threads will give you an idea on a number of analysis methods and also an initial idea on how to play around with your data.