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Are there any good places to find publicly and freely available transcriptome datasets including the raw reads preferably Illumina, for the purposes of publishing a resource paper?
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Check out : http://www.ncbi.nlm.nih.gov/geo/quer...i?acc=GSE29158
You can download the raw reads.
This is this study : Toung JM, Morley M, Li M, Cheung VG. RNA-sequence analysis of human B-cells. Genome Res 2011 Jun;21(6):991-8. PMID: 21536721
It's the RNA seq of several "Coriell CEPH B-Cell" cell lines; so it's theoretically close to "normal rna-seq".
I used a model based alignment of this data to the genome (genome+refome+altspliceome+estome) approach.
These results are viewable at Cancer Genome Workbench under hg19 , "Cancer Genome Workbench - Miscellaneous Tracks" , UPENN_BCELL_NG_RNA
Just click on this URL ...
You can zoom in and right click on the tracks to use Bambino to view the details.
This is one of the few good PUBLIC human rnaseq datasets. A lot of data is secret under US privacy laws.Last edited by Richard Finney; 03-21-2012, 09:44 AM. -
Thanks! that is pretty close to what I am looking for.Originally posted by Richard Finney View PostCheck out : http://www.ncbi.nlm.nih.gov/geo/quer...i?acc=GSE29158
You can download the raw reads.
This is this study : Toung JM, Morley M, Li M, Cheung VG. RNA-sequence analysis of human B-cells. Genome Res 2011 Jun;21(6):991-8. PMID: 21536721
It's the RNA seq of several "Coriell CEPH B-Cell" cell lines; so it's theoretically close to "normal rna-seq".
I used a model based alignment of this data to the genome (genome+refome+altspliceome+estome) approach.
These results are viewable at Cancer Genome Workbench under hg19 , "Cancer Genome Workbench - Miscellaneous Tracks" , UPENN_BCELL_NG_RNA
Just click on this URL ...
You can zoom in and right click on the tracks to use Bambino to view the details.
This is one of the few good PUBLIC human rnaseq datasets. A lot of data is secret under US privacy laws.Comment
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Hi, are there any good places to find freely RNA-seq data of all or many different human cell lines ,and RNA-seq data of all or many different human tissue? If NCBI database can find this, how can I to find all these data?
I am looking forward to your reply. Best wishes! Thank you!Comment
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A good staring pint might be the ReCount resource: http://bowtie-bio.sourceforge.net/recount/
For different cell lines, look at the Encode project, and for different tissue types, maybe at the paper by Brawand et al. (Nature, 2011).Comment
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Well you can try out the link given below. May be it can work. It contains important information on transcriptome data sets. I get to know so much in detail about these data sets and believe me it's really good to know so much about it.Last edited by Geoffreyion; 06-04-2013, 12:20 AM.click here >>> Light in the box coupon codeComment
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Love this - good data definitely starts from good input, and poor input can only give relatively poor data. I particularly like the mention of Nanodrop/absorbance based methods for quantification. It's such a toss up if you'll get an accurate reading or what amounts to a randomly generated number, and a lot of library/sequencing related issues can be traced back to poor quant.Yesterday, 11:43 AM
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I’m not a sequencing expert. I’m a purification scientist who uses NGS to evaluate workflows my group develops. With this perspective, we think about the sample first and the NGS workflow second. The sequencer is an exceptionally honest reporter, but it can only report on what you give it, so whether you get clean, interpretable data from an NGS workflow is largely determined before you begin.
Here are nine questions we think about, in roughly the order they matter, before...
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