Seqanswers Leaderboard Ad

Collapse

Announcement

Collapse
No announcement yet.
X
 
  • Filter
  • Time
  • Show
Clear All
new posts

  • #16
    Originally posted by michfish86 View Post
    Edit: Could the reason for the lack of matching to the reference transcriptome just be the presence of novel transcripts in my samples that were not present in the individuals in the other study that generated the reference? For instance, because the reference may not have included the specific type of tissue that I'm evaluating?
    While that is tempting do you have reasons to suspect that may be case. Is the genome odd (large with multiple chromosomes, ploidy difference)?

    Even though you may not have enough data you could try a de novo assembly and see what you get. Be sure to map the reads back to your own assembly to see what percentage of them map?

    Comment


    • #17
      Originally posted by GenoMax View Post
      Where do you see the 20% map?
      I think Macspider's phrasing a just a little confusing. I think s/he means that more than 20% of my reads are not mapping.

      Comment


      • #18
        Originally posted by GenoMax View Post
        While that is tempting do you have reasons to suspect that may be case. Is the genome odd (large with multiple chromosomes, ploidy difference)?
        Looking back at the paper that accompanies the reference transcriptome, they used several different tissue types, but did not include the exact tissue that I sequenced. The genome isn't particularly huge (C-value 4.75), but the chromosomal arraignments have been tough to nail down. One study that looked into it found a diploid number of 110 with a range of 94-185.

        Even though you may not have enough data you could try a de novo assembly and see what you get. Be sure to map the reads back to your own assembly to see what percentage of them map?
        I will give it a shot.

        Thanks again!!

        Comment


        • #19
          BBMap suite has seal.sh and tadpole.sh. You may want to look at them as substitute assemblers (though trinity has been the assembler of choice for eukaryotes of late).

          Comment


          • #20
            While my de novo assembly runs, I wanted to get clarification on a what could be causing the large difference in alignment percentage between Bowtie and Bowtie2 and BBMap. Reminder of alignment scores below:

            Bowtie: 43%
            Bowtie2: 71%
            BBMap: 78%

            I keep seeing that Bowtie2 and BBMap are "more sensitive" or "more flexible" but I can't figure out what that means and I'm skeptical of the higher alignment scores because I'm afraid of including a bunch of false positives.

            Two potential reasons that I'm aware of for Bowtie being substantially lower is because Bowtie doesn't allow ambiguous characters (e.g., N) in alignments and it disqualifies discordant reads, whereas Bowtie2 still seeks alignments despite these imperfections. I'd appreciate any additional insight in what could be causing these disparities since I don't want to blindly accept the higher alignment scores just because they're higher!

            Edit: Update: Running Bowtie2 with the --no-mixed option turned on reduces the alignment percent to 54%. It appears that Bowtie is "--no-mixed" by default, therefore this could be a major contributor to the difference between my Bowtie and Bowtie2 percentages. In "--no-mixed" mode, alignments must involve both pairs of reads, therefore, in Bowtie I may be losing some reads just because only one of the reads constituting a "pair" aligns. Again, I'd appreciate anyone else's insights.
            Last edited by michfish86; 08-25-2016, 12:12 PM.

            Comment

            Latest Articles

            Collapse

            • seqadmin
              The Impact of AI in Genomic Medicine
              by seqadmin



              Artificial intelligence (AI) has evolved from a futuristic vision to a mainstream technology, highlighted by the introduction of tools like OpenAI's ChatGPT and Google's Gemini. In recent years, AI has become increasingly integrated into the field of genomics. This integration has enabled new scientific discoveries while simultaneously raising important ethical questions1. Interviews with two researchers at the center of this intersection provide insightful perspectives into...
              02-26-2024, 02:07 PM
            • seqadmin
              Multiomics Techniques Advancing Disease Research
              by seqadmin


              New and advanced multiomics tools and technologies have opened new avenues of research and markedly enhanced various disciplines such as disease research and precision medicine1. The practice of merging diverse data from various ‘omes increasingly provides a more holistic understanding of biological systems. As Maddison Masaeli, Co-Founder and CEO at Deepcell, aptly noted, “You can't explain biology in its complex form with one modality.”

              A major leap in the field has
              ...
              02-08-2024, 06:33 AM

            ad_right_rmr

            Collapse

            News

            Collapse

            Topics Statistics Last Post
            Started by seqadmin, Today, 06:12 AM
            0 responses
            13 views
            0 likes
            Last Post seqadmin  
            Started by seqadmin, 02-23-2024, 04:11 PM
            0 responses
            64 views
            0 likes
            Last Post seqadmin  
            Started by seqadmin, 02-21-2024, 08:52 AM
            0 responses
            70 views
            0 likes
            Last Post seqadmin  
            Started by seqadmin, 02-20-2024, 08:57 AM
            0 responses
            60 views
            0 likes
            Last Post seqadmin  
            Working...
            X