Try blast2go Is very user friendly.

TMeV - very user friendly, good on analysis methods, not much on preprocessing;

Bioconductor - not so user friendly but still good;

For co-expression and functional network analyses you a have FunNet. http://funnet.ws

or GenePattern

Firstly you de novo assembly of your short reads using CLCbio Genomics Workbench or any freely available software, than for annotation use another programme as Dr. Ricardo suggest.

T mev good for numerous analysis methods. easy to use.

You can input your data into MG-RAST.

I also used CLC Bio Genomics Workbench for mapping the reads to reference genomes.

You could try Galaxy (https://main.g2.bx.psu.edu/). Galaxy provides a number of tools for short read mapping and further downstream analyses.

Try MeV or MapMan : two softwares very easy to use and quite useful !

if you have a reference genome, you could try the pipeline Bowtie, Tophat and Cufflinks at the CBCB http://www.cbcb.umd.edu/software/

http://www.cbcb.umd.edu/software/

http://tophat.cbcb.umd.edu/

http://cufflinks.cbcb.umd.edu/

It is an open source software package, not very user friendly . You can align read with Bowtie, map splice junctions with Tophat and estimate transcript abundances with Cufflinks

http://biowhat.ucsd.edu/homer/ngs/homerTools.html

Expander - http://acgt.cs.tau.ac.il/expander/expander.html

MEV can be a good start see http://www.tm4.org/mev/

Try searching open access journals in http://www.doaj.org

Rnnotator on Galaxy, or on the command-line

https://galaxy.jgi-psf.org/root?tool_id=jgi_rnd_rnaseq_counting

The shortcuts can be often misleading, talk to your local bioinformatician a lot or find one who is patient enough :)

If you have sequencing data on input (BAM files) try perhaps with basic modules on Galaxy, depending what you want to see. Use a lot of genome browsers (IGV, UCSC) to verify your findings looking at the coverage of reads for your favourite genes.

try MIRA, its easy, no installation needed, juz follow the definitive guide n you can get the results in few hours, depending on your system. for viewing your assembly, try tablet. for blasting, blast2go and then GO. your assembly is done. AL THE BEST!!

You could try our PathVisio, which is available from pathvisio.org. It uses pathways from wikipathways.org and mapping databases based on ENSEMBL.

I only realised after rereading that that will only be useful after you processedd your reads using one of the other methods metioned, so you have processed gene expression values, sorry about that.

A easy way to explore some published microarray data:

Transcriptome Browser: http://www.plosone.org/article/info:doi%2F10.1371%2Fjournal.pone.0004001

To analyse your data:

TM4-MeV: www.tm4.org/mev/

CuffLinks is a popular tool for analyzing RNA-seq data, and has a Nature Protocols article describing how to use it. An RNA-seq package called edgeR is also available for the widely used Bioconductor data analysis software. These are all open source.

http://cufflinks.cbcb.umd.edu/

http://www.nature.com/nprot/journal/v7/n3/full/nprot.2012.016.html

http://www.bioconductor.org/

http://www.bioconductor.org/packages/release/bioc/html/edgeR.html

Hello,

For transcriptome analysis follow these steps and I think you should be able to do the analysis yourself.

First map you reads using a software called Tophat which does alignning using Bowtie.

Then calculate the differential gene expression using Cufflink.

If you want to compare your data then you can also use Cuffcompare.

Information about these software is available at following links:

Tophat

http://tophat.cbcb.umd.edu/

Cufflink

http://cufflinks.cbcb.umd.edu/

Hope this will be useful for you.

Neha

http://www.linkedin.com/pub/qing-rong-tim-liu/a/351/36

The Database for Annotation, Visualization and Integrated Discovery (DAVID ) v6.7 is an update to the sixth version of our original web-accessible programs.

For more downstream applications, an option would be EXPANDER

http://acgt.cs.tau.ac.il/expander/

Very user-friendly clustering tool which allows for analysing transcription factor enrichment, GO/KEGG and many other things

You could try FunNet http://funnet.ws

It allows handling functional and co-expression network analyses. It is a web interface that uses an R package with the same name.

MeV from the TM4 suite is very user-friendly (I use it for teaching), and has a broad range of analysis tools, including a recently-developped one for RNA-Seq.

It works fine on PC, MAC and Linux.

http://www.tm4.org/mev/

I had very little bioinformatic knowledge when I analysed my transcriptomic data but I found DAVID and KEGG both very easy to use for identifying pathways and biological processes. However, to perform stats I used EdgeR which does need knowledge on script writing but if you can find someone to help you out with it is very good.

http://www.genetics.ucla.edu/labs/horvath/CoexpressionNetwork/Rpackages/WGCNA/

Dear Dr. Chaubal

Thank you very much for extending your helpng hand to me. Here is my mail id: [email protected]. Could you kindly drop a mail to me please.

For assembly of transcriptome data you cant go wrong with Tophat and cufflinks. For Annotation and general mining you could try Blast2Go (Blast analysis,GO term mapping, InterProScans and much more). Particularly good for getting a general idea of the composition of a transcriptome.

I used Genevestigator. is very friendly and helpful for interpretation of transcriptome data.

There are so many user-friendly softwares for analyzing transcriptome data. I will recommend that you check through the M.Sc thesis of Kristen Johnson. Check the link below:

http://scholarworks.uno.edu/cgi/viewcontent.cgi?article=2463&context=td

Try blast2go

Can anyone suggest tool and its ideal parameters for transcriptome sequence assembly?

RobinA is fantastic

I suppose that you can try the SOAP(Short Oligonucleotide Analysis Package ). It is really useful for DNA, RNA aglignment, SNP calling, de novo assembly. You can check this website (http://soap.genomics.org.cn/) and download the newly updated version. It is all for free. May this informtion helps.

If you want differential expression analysis then go with Bioinconductor one-Chanel GUI version and you can also go with RobiNA tool. currently, using RobiNA (http://mapman.gabipd.org/web/guest/robin)it is possible to analyse Illumina/Solexa-based RNA-Seq data (supplied in FASTQ format), Affymetrix data and generic tabular two color or single channel array data.May this information hepls you.

For annotation of the assembled transcriptome (protein, domain, GO terms) I will recommend a pipeline recently published by my group

Publication: http://www.ncbi.nlm.nih.gov/pubmed/25701574

Available at: https://github.com/frankMusacchia/Annocript

Mailing list: https://groups.google.com/forum/#!forum/annocript

Once configured the pipeline is completely automated with a drastically reduced annotation time period compared to other pipelines.

MEV can be a good start

I used Genevestigator. is very friendly and helpful for interpretation of transcriptome data.

Trinity for denovo transcriptome analysis. A complete workflow for RNA Seq data

Hi Arjun, if you are a beginner at transcriptomics, I think you can start with galaxy, which is a free web-based platform for transcriptomics., you don't need to learn to code for that. Once you get used to it then you can start with the shell-based and R tools like HISAT2, FeatureCounts, DESeq2, etc.