I am Searching collaborator for RNA seq. data analysis. As I am trying to learn about statistical analysis of RNA seq. data and finding it way difficult. If any one help me out in this can share the authorship with him/her.
Dear Harsrhaj,
You may contact following researchers:
https://www.researchgate.net/profile/Swarnendu_Chandra
https://www.researchgate.net/profile/Arun_Dutta3
Best Regards,
P
Dear Harsrhaj,
There are commercially available packages which are quite intuitive.
Partek Flow was built specifically for RNA-Seq analysis. The methods included are filtering, mapping reads to a genomic reference, counting read matches to transcripts/genes, QC, coverage analysis, visualization, and differential expression to name a few. They include robust statistical analyses which is what Partek is known for.
http://www.partek.com/partekflow
Yes, there is a cost associated but the ease of use may justify.
There are open source solutions which are free as well such as Bioconductor which is part of the R statistical framework. These packages mostly handle all analysis post-mapping.
Lastly, there is a comprehensive tutorial which started on the SeqAnswers blog but is now in a WikiBooks entry.
https://en.wikibooks.org/wiki/Next_Generation_Sequencing_(NGS)/RNA
I hope this helps.
Best,
Jeff
Thank you Prakash Pradhan and Jeoffrey J Schageman for your information
A good starting point would be this review
http://www.genomebiology.com/2010/11/12/220
Forgot about this Oshlack paper Praveen. Also a great read.
Jeff
Hi,
regarding RNASeq pipeline for gene expression, transcriptome and/or alternative splicing data analysis, galaxy provide a useful work environment. I invite you to try your analysis considering this tool.
Dear Harsrhaj,
we have developed an online tool named AIR (Artificial Intelligence RNAseq) specifically aimed to all the scientists with no expertise in bioinformatics and RNA-seq data analysis. AIR let you perform all the steps from pre-processing to differential expression analysis on more than 45,000 genomes in few hours. Please give it a look: https://transcriptomics.sequentiabiotech.com/
Kind regards
Over the period of time, I acquired some skills in NGS data analysis. Way to go!
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