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  • ERANGE and other packages for RNAseq analysis

    Hi everyone,

    I am currently exploring the ERANGE package and was wondering whether there are other available packages like this to identify new regions and calculate statistics based on read counts.

    Secondly, can this be applied to sequencing technologies other than Illumina? I havent recieved a reply from the authors so I figured I would ask the forum I was thinking of using SOLiD data which is roughly the same length as the illumina reads. Out of interest has anyone tried to use the package with other technologies?

  • #2
    Can you be a little more specific about what you want to do with RNA-Seq? There are a couple of software packages that are available, depending on what your interests are.

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    • #3
      Originally posted by rs705 View Post
      Can you be a little more specific about what you want to do with RNA-Seq? There are a couple of software packages that are available, depending on what your interests are.
      At the moment I'm just checking out whats available so I'd be interested in any packages that process RNA data. I'm looking for a package that attributes reads to a gene then calculates statistics like RPKM for the gene and uses read clustering to identify novel exons etc. Like I said, I'm more interested in knowing what is available for RNAseq than the specific function.

      Comment


      • #4
        ERANGE for non-Illumina data

        Hi Warren,

        I'm sorry if I didn't get back to you by email!

        I certainly don't have any explicit support for SOLiD colorspace; since we only have Illumina sequencers at Caltech, I don't even have the data and tools to support it even if I wished.

        But, assuming that you could dump the reads out of colorspace into fasta/fastq, then you should be able to map the reads against a reference genome (or reference+splice junction, aka an "expanded genome") using bowtie and then proceed with the rest of ERANGE !

        There are several other packages out there that are just starting to appear. TopHat is another one that has support for RPKM, etc.... As far as I know, it also needs a reference genome & start from fasta/fastq.

        Ali

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        • #5
          Originally posted by alim View Post
          Hi Warren,

          I'm sorry if I didn't get back to you by email!

          I certainly don't have any explicit support for SOLiD colorspace; since we only have Illumina sequencers at Caltech, I don't even have the data and tools to support it even if I wished.

          But, assuming that you could dump the reads out of colorspace into fasta/fastq, then you should be able to map the reads against a reference genome (or reference+splice junction, aka an "expanded genome") using bowtie and then proceed with the rest of ERANGE !

          There are several other packages out there that are just starting to appear. TopHat is another one that has support for RPKM, etc.... As far as I know, it also needs a reference genome & start from fasta/fastq.

          Ali
          Hi Ali,

          Thanks for the response. I have checked out TopHat which also looks like quite an interesting package. I was wondering as well about using something like 454 with ERANGE since the read lengths vary can it still be used with the ERANGE package? I am specifically concerned about the creation of splice-reads and what value to select for the splice radius, if you have any thoughts please let me know.

          Thanks again!

          Comment


          • #6
            Hi Warren,

            ERANGE currently assumes a fixed read length & isn't particularly mixed read-length friendly. It's a topic that's been on my mind a lot lately and I plan on fixing it.

            Some of these problems relate to read-length in a direct way.

            When reads are less than 32bp long, few enough reads cross-splices that we need the splice-junctions explicitly in order to recover the known splices (notice that the TopHat developers are very happy to recover 80% of the known splices that ERANGE sees) and de novo splice discovery has a very high false-positive rate.

            As reads get in the 40-75 bp range, you can now map novel splices with some good confidence.

            But as reads get longer, an increasing fraction of reads cross more than one splice.... one of the upcoming versions of ERANGE will deal with that.

            If your reads are long enough, then ERANGE now supports a splice-junction free way of mapping splices (which is described in the ERANGE README.build-rds help file). Essentially, just map the reads on the regular genome with bowtie, explicitly saving the unmapped reads in a separate file. Then map those reads with blat (yes, it's slow) and only import those that map well onto the genome & that have an intron.

            Ali

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            • #7
              RPKM-normalization

              Please, how do to normalize the data from SOLiD? I'll do differential expression. RPKM is the standardization? What does that mean exactly
              thanks

              Comment


              • #8
                Solid is currently only supported through bowtie's (0.12.X) support for colorspace
                Maintainer of ERANGE and Cistematic
                Software Engineer, Division of Biology
                California Institute of Technology

                Comment


                • #9
                  miRanalyzer standalone download

                  Hi,

                  I am trying to install miRanalyzer stand alone version. I have built the database and managed to download all required tools and packages. When I tried to run it with the test data provided, I get this message: "Failed to load Main-Class manifest attribute from miRanalyzer.jar
                  ". Just wondering what I am doing wrong

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                  • #10
                    HI All
                    How can I normalize differential Expression (log2) values from Cuffdiffs. I dont have replicate and am not good in unix based systems

                    Comment


                    • #11
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