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  1. IGB
  2. IGBF-3044

Investigate: Alternative splicing statistical analysis

    Details

    • Type: Task
    • Status: Closed (View Workflow)
    • Priority: Major
    • Resolution: Done
    • Affects Version/s: None
    • Fix Version/s: None
    • Labels:
      None

      Description

      The Loraine Lab has developed alternative splicing RNA-Seq analysis tools called "find_junctions" and "arabitag" that we've used in conjunction with statistical testing to detect when splicing changes in an experiment.

      This software works OK but interpreting results when one gene has multiple alternative splicing choices is difficult. Another potential weakness is the statistical test we use to detect a change across conditions. To test for a change, we compare proportion means using a t-test, after converting the proportions data to something more normal, using a transformation. In practice, this works OK, but things get confusing when we have multiple splicing patterns affect the same region of a gene, as we end up comparing each option pairwise against each other option. This is not a deal-breaker, but it would be nice if we could perform a single test even for alternative splicing choices where there are more than two options. There may be better software or better methods we can use instead.

      However, one thing to always keep in mind is that we mainly care about understanding how and if splicing is regulated, and in detecting changes in the splicing machinery's function. In this case, what matters ultimately the frequency with which individual splice sites get used relative to alternative options, and what causes this frequency to change. Currently, we assess splice site selection frequency by counting relevant reads and ignoring both irrelevant reads, such as reads that align outside the differentially spliced regions, or reads we can't assign to a single choice. Moreover, because of the complexity of splicing and because of the unknowableness of reads mapping far away from a given splice site, we ought to focus our attention on the reads for which we are most confident in their mapping. What we care about the most is whether or not the underlying frequency of splice site usage changes between treatments or conditions. It's nice if we can know what that frequency is most likely to be, but a very rough estimate of the actual value is fine. Again, we care about the fact of a change, because the change signals that something biologically interesting might be happening.

      For this task, let's scan the papers found in the literature review results (see: IGBF-3041) to identify alternative splicing analysis software packages and determine: Which of these, if any, should we explore as an alternative to the find junctions pipeline?

      Also, let's investigate the statistics literature to determine if the test we need is already developed for an analogous setting that we can deploy for ourselves. We already have software that counts and reports relevant read alignments (see: arabitag), and so really we only need a good way to test for differences in splicing across conditions.

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        1. 3044.xlsx
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          Nowlan Freese
        2. Mosaic.jpeg
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          Ann Loraine

          Activity

          ann.loraine Ann Loraine created issue -
          ann.loraine Ann Loraine made changes -
          Field Original Value New Value
          Epic Link IGBF-3039 [ 21553 ]
          ann.loraine Ann Loraine made changes -
          Sprint Spring 1 2022 Jan 3 - Jan 14 [ 136 ]
          ann.loraine Ann Loraine made changes -
          Rank Ranked lower
          ann.loraine Ann Loraine made changes -
          Description The Loraine Lab has developed an alternative splicing RNA-Seq analysis tool called "find_junctions" that we've used in conjunction with statistical testing to detect when splicing changes in an experiment.

          This software works OK but interpreting results when one gene has multiple alternative splicing choices is difficult. There may be better software we can use instead.

          For this task, use the literature review results to identify alternative splicing analysis software packages and determine: Which of these, if any, should we explore as an alternative to the find junctions pipeline?
          The Loraine Lab has developed alternative splicing RNA-Seq analysis tools called "find_junctions" and "arabitag" that we've used in conjunction with statistical testing to detect when splicing changes in an experiment.

          This software works OK but interpreting results when one gene has multiple alternative splicing choices is difficult. Another potential weakness is the statistical test we use to detect a change across conditions. To test for a change, we compare proportion means using a t-test, after converting the proportions data to something more normal, using a transformation. In practice, this works OK, but things get confusing when we have multiple splicing patterns affect the same region of a gene, as we end up comparing each option pairwise against each other option. Another weakness is that the test does not take into account the number of informative reads collected. There may be better software or better methods we can use instead.

          For this task, use the literature review results to identify alternative splicing analysis software packages and determine: Which of these, if any, should we explore as an alternative to the find junctions pipeline?
          ann.loraine Ann Loraine made changes -
          Description The Loraine Lab has developed alternative splicing RNA-Seq analysis tools called "find_junctions" and "arabitag" that we've used in conjunction with statistical testing to detect when splicing changes in an experiment.

          This software works OK but interpreting results when one gene has multiple alternative splicing choices is difficult. Another potential weakness is the statistical test we use to detect a change across conditions. To test for a change, we compare proportion means using a t-test, after converting the proportions data to something more normal, using a transformation. In practice, this works OK, but things get confusing when we have multiple splicing patterns affect the same region of a gene, as we end up comparing each option pairwise against each other option. Another weakness is that the test does not take into account the number of informative reads collected. There may be better software or better methods we can use instead.

          For this task, use the literature review results to identify alternative splicing analysis software packages and determine: Which of these, if any, should we explore as an alternative to the find junctions pipeline?
          The Loraine Lab has developed alternative splicing RNA-Seq analysis tools called "find_junctions" and "arabitag" that we've used in conjunction with statistical testing to detect when splicing changes in an experiment.

          This software works OK but interpreting results when one gene has multiple alternative splicing choices is difficult. Another potential weakness is the statistical test we use to detect a change across conditions. To test for a change, we compare proportion means using a t-test, after converting the proportions data to something more normal, using a transformation. In practice, this works OK, but things get confusing when we have multiple splicing patterns affect the same region of a gene, as we end up comparing each option pairwise against each other option. Another weakness is that the test does not take into account the number of informative reads collected. There may be better software or better methods we can use instead.

          For this task, use the literature review results to identify alternative splicing analysis software packages and determine: Which of these, if any, should we explore as an alternative to the find junctions pipeline?

          Also, investigate the statistics literature to determine if the test we need is already developed.
          ann.loraine Ann Loraine made changes -
          Description The Loraine Lab has developed alternative splicing RNA-Seq analysis tools called "find_junctions" and "arabitag" that we've used in conjunction with statistical testing to detect when splicing changes in an experiment.

          This software works OK but interpreting results when one gene has multiple alternative splicing choices is difficult. Another potential weakness is the statistical test we use to detect a change across conditions. To test for a change, we compare proportion means using a t-test, after converting the proportions data to something more normal, using a transformation. In practice, this works OK, but things get confusing when we have multiple splicing patterns affect the same region of a gene, as we end up comparing each option pairwise against each other option. Another weakness is that the test does not take into account the number of informative reads collected. There may be better software or better methods we can use instead.

          For this task, use the literature review results to identify alternative splicing analysis software packages and determine: Which of these, if any, should we explore as an alternative to the find junctions pipeline?

          Also, investigate the statistics literature to determine if the test we need is already developed.
          The Loraine Lab has developed alternative splicing RNA-Seq analysis tools called "find_junctions" and "arabitag" that we've used in conjunction with statistical testing to detect when splicing changes in an experiment.

          This software works OK but interpreting results when one gene has multiple alternative splicing choices is difficult. Another potential weakness is the statistical test we use to detect a change across conditions. To test for a change, we compare proportion means using a t-test, after converting the proportions data to something more normal, using a transformation. In practice, this works OK, but things get confusing when we have multiple splicing patterns affect the same region of a gene, as we end up comparing each option pairwise against each other option. Another weakness is that the test does not take into account the number of informative reads collected. There may be better software or better methods we can use instead.

          For this task, use the literature review results to identify alternative splicing analysis software packages and determine: Which of these, if any, should we explore as an alternative to the find junctions pipeline?

          Also, investigate the statistics literature to determine if the test we need is already developed for an analogous setting that we can deploy for ourselves.
          ann.loraine Ann Loraine made changes -
          Summary Investigate: Alternative splicing statistical analysis tools Investigate: Alternative splicing statistical analysis
          ann.loraine Ann Loraine made changes -
          Assignee Ann Loraine [ aloraine ]
          ann.loraine Ann Loraine made changes -
          Status To-Do [ 10305 ] In Progress [ 3 ]
          ann.loraine Ann Loraine made changes -
          Description The Loraine Lab has developed alternative splicing RNA-Seq analysis tools called "find_junctions" and "arabitag" that we've used in conjunction with statistical testing to detect when splicing changes in an experiment.

          This software works OK but interpreting results when one gene has multiple alternative splicing choices is difficult. Another potential weakness is the statistical test we use to detect a change across conditions. To test for a change, we compare proportion means using a t-test, after converting the proportions data to something more normal, using a transformation. In practice, this works OK, but things get confusing when we have multiple splicing patterns affect the same region of a gene, as we end up comparing each option pairwise against each other option. Another weakness is that the test does not take into account the number of informative reads collected. There may be better software or better methods we can use instead.

          For this task, use the literature review results to identify alternative splicing analysis software packages and determine: Which of these, if any, should we explore as an alternative to the find junctions pipeline?

          Also, investigate the statistics literature to determine if the test we need is already developed for an analogous setting that we can deploy for ourselves.
          The Loraine Lab has developed alternative splicing RNA-Seq analysis tools called "find_junctions" and "arabitag" that we've used in conjunction with statistical testing to detect when splicing changes in an experiment.

          This software works OK but interpreting results when one gene has multiple alternative splicing choices is difficult. Another potential weakness is the statistical test we use to detect a change across conditions. To test for a change, we compare proportion means using a t-test, after converting the proportions data to something more normal, using a transformation. In practice, this works OK, but things get confusing when we have multiple splicing patterns affect the same region of a gene, as we end up comparing each option pairwise against each other option. This is not a deal-breaker, but it would be nice if we could perform a single test even for alternative splicing choices where there are more than two options. There may be better software or better methods we can use instead.

          However, one thing to always keep in mind is that we mainly care about understanding how and if splicing is regulated, and in detecting changes in the splicing machinery's function. In this case, what matters ultimately the frequency with which individual splice sites get used relative to alternative options, and what causes this frequency to change. Currently, we assess splice site selection frequency by counting relevant reads and ignoring both irrelevant reads, such as reads that align outside the differentially spliced regions, or reads we can't assign to a single choice. Moreover, because of the complexity of splicing and because of the unknowableness of reads mapping far away from a given splice site, we ought to focus our attention on the reads for which we are most confident in their mapping. What we care about the most is whether or not the underlying frequency of splice site usage changes between treatments or conditions. It's nice if we can know what that frequency is most likely to be, but a very rough estimate of the actual value is fine. Again, we care about the fact of a change, because the change signals that something biologically interesting might be happening.

          For this task, let's scan the papers found in the literature review results (see: IGBF-3041) to identify alternative splicing analysis software packages and determine: Which of these, if any, should we explore as an alternative to the find junctions pipeline?

          Also, let's investigate the statistics literature to determine if the test we need is already developed for an analogous setting that we can deploy for ourselves. We already have software that counts and reports relevant read alignments (see: [arabitag|https://bitbucket.org/lorainelab/altspliceanalysis]), and so really we only need a good way to test for differences in splicing across conditions.
          ann.loraine Ann Loraine made changes -
          Attachment Mosaic.jpeg [ 17048 ]
          ann.loraine Ann Loraine made changes -
          Comment [ If we care about how splicing is regulated, and in detecting changes in the splicing machinery's function, then what matters ultimately is the frequency with which individual splice sites get used relative to alternative options. We can assess splice site selection frequency by counting relevant reads and ignoring both irrelevant reads, such as reads that align the differentially spliced regions, or reads we can't assign to a single choice. Moreover, because of the complexity of splicing and because of the unknowableness of reads mapping far away from a given splice site, we ought to focus our attention on the reads for which we are most confident in their mapping. What we care about the most is whether or not the underlying frequency of splice site usage changes between treatments or conditions. It's nice if we can know what that frequency is most likely to be, but a very rough estimate of the actual value is fine. Again, we care about the fact of a change, because the change signals that something biologically interesting might be happening. ]
          ann.loraine Ann Loraine made changes -
          Status In Progress [ 3 ] Needs 1st Level Review [ 10005 ]
          ann.loraine Ann Loraine made changes -
          Assignee Ann Loraine [ aloraine ]
          ann.loraine Ann Loraine made changes -
          Status Needs 1st Level Review [ 10005 ] First Level Review in Progress [ 10301 ]
          ann.loraine Ann Loraine made changes -
          Status First Level Review in Progress [ 10301 ] To-Do [ 10305 ]
          ann.loraine Ann Loraine made changes -
          Assignee Ann Loraine [ aloraine ]
          ann.loraine Ann Loraine made changes -
          Status To-Do [ 10305 ] In Progress [ 3 ]
          ann.loraine Ann Loraine made changes -
          Status In Progress [ 3 ] To-Do [ 10305 ]
          ann.loraine Ann Loraine made changes -
          Assignee Ann Loraine [ aloraine ]
          nfreese Nowlan Freese made changes -
          Status To-Do [ 10305 ] In Progress [ 3 ]
          nfreese Nowlan Freese made changes -
          Assignee Nowlan Freese [ nfreese ]
          nfreese Nowlan Freese made changes -
          Attachment 3044.xlsx [ 17068 ]
          nfreese Nowlan Freese made changes -
          Assignee Nowlan Freese [ nfreese ]
          nfreese Nowlan Freese made changes -
          Status In Progress [ 3 ] Needs 1st Level Review [ 10005 ]
          ann.loraine Ann Loraine made changes -
          Sprint Spring 1 2022 Jan 3 - Jan 14 [ 136 ] Spring 1 2022 Jan 3 - Jan 14, Spring 2 2022 Jan 18 - Jan 28 [ 136, 137 ]
          ann.loraine Ann Loraine made changes -
          Rank Ranked higher
          ann.loraine Ann Loraine made changes -
          Status Needs 1st Level Review [ 10005 ] First Level Review in Progress [ 10301 ]
          ann.loraine Ann Loraine made changes -
          Status First Level Review in Progress [ 10301 ] Ready for Pull Request [ 10304 ]
          ann.loraine Ann Loraine made changes -
          Status Ready for Pull Request [ 10304 ] Pull Request Submitted [ 10101 ]
          ann.loraine Ann Loraine made changes -
          Status Pull Request Submitted [ 10101 ] Reviewing Pull Request [ 10303 ]
          ann.loraine Ann Loraine made changes -
          Status Reviewing Pull Request [ 10303 ] Merged Needs Testing [ 10002 ]
          ann.loraine Ann Loraine made changes -
          Status Merged Needs Testing [ 10002 ] Post-merge Testing In Progress [ 10003 ]
          ann.loraine Ann Loraine made changes -
          Resolution Done [ 10000 ]
          Status Post-merge Testing In Progress [ 10003 ] Closed [ 6 ]
          ann.loraine Ann Loraine made changes -
          Assignee Ann Loraine [ aloraine ]

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              ann.loraine Ann Loraine
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              ann.loraine Ann Loraine
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