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Transcriptomic Diversity Summaries

Source: R/IsoformicExperiment-diversity.R
diversity.Rd

These generics quantify how expression is distributed across the isoforms of each gene, which is the question an IsoformicExperiment is built to answer. All computations use matrix operations on the cached assays and scale to full transcriptome experiments.

  • isoform_fraction(x): matrix (transcripts x samples) of the fraction of its gene's expression carried by each transcript. NA where the gene is not expressed in a sample.

  • tx_diversity(x): one row per gene summarising isoform usage: number of annotated, assayed and expressed isoforms, number of transcript types, the dominant isoform and its mean fraction, and the effective number of isoforms (exp(Shannon entropy) of the mean isoform fractions, 1 = a single isoform carries all expression).

  • dominant_isoform(x, group): the dominant isoform of each gene, overall or per level of a col_data column, flagging genes whose dominant isoform changes between groups (dominant_switch).

  • isoform_switches(x): relates transcript- and gene-level differential expression per gene: counts of significant isoforms up and down, the gene-level call and a switch_type classification ("opposite_direction", "det_not_deg", "consistent").

  • exon_diversity(x, gene_name): per gene, the number of distinct exons, how many are constitutive (shared by all isoforms) versus alternative, and the mean number of exons per isoform.

  • haplotype_summary(x, group): for haplotype-resolved annotations (see merge_annotations()), expression of each gene per haplotype, the haplotype fraction (allelic imbalance), the dominant isoform of each haplotype (compared through source_transcript_id) and whether the dominant isoform differs between haplotypes (haplotype_isoform_switch). Genes are matched across haplotypes by source_gene_id, falling back to gene_name.

dominant_isoform() also reports dominant_is_canonical, whether the dominant isoform is the MANE Select / Ensembl canonical / RefSeq Select transcript of its gene. When the object carries uncertainty tables (see add_uncertainty()) it adds dominant_inf_rv, the inferential relative variance of the dominant isoform, and dominant_ambiguous, whether it cannot be told apart from a sibling isoform. isoform_switches() adds n_det_confident, the number of significant isoforms with high confidence, once de_confidence() results are stored.

Usage

isoform_fraction(self, assay = "abundance", ...)

tx_diversity(
  self,
  assay = "abundance",
  min_expr = 1,
  min_samples = 1L,
  gene_name = NULL,
  ...
)

dominant_isoform(
  self,
  group = NULL,
  assay = "abundance",
  gene_name = NULL,
  min_expr = 0,
  ...
)

isoform_switches(self, gene_name = NULL, confident_only = FALSE, ...)

exon_diversity(self, gene_name = NULL, ...)

haplotype_summary(
  self,
  group = NULL,
  assay = "abundance",
  gene_name = NULL,
  ...
)

Arguments

self

An IsoformicExperiment.

assay

Name of the transcript assay to use (default "abundance", falling back to the first assay).

...

Passed on to methods.

min_expr

Minimum assay value for a transcript to count as expressed in a sample.

min_samples

Minimum number of samples in which a transcript must be expressed to count as expressed.

gene_name

Optional character vector of gene names or IDs to restrict the result to.

group

Name of a col_data column defining sample groups, or NULL for all samples together.

confident_only

Logical. Count only the significant isoforms with high confidence (see de_confidence()) in isoform_switches().

Value

A matrix for isoform_fraction(), tibbles otherwise.

Examples

iso <- example_isoformic()
isoform_fraction(iso)[1:3, 1:3]
#>                   SRR11498039 SRR11498040 SRR11498041
#> ENST00000374514.8  0.96675753  0.98117418  0.98239081
#> ENST00000420982.5  0.00000000  0.00000000  0.00000000
#> ENST00000374502.7  0.02265948  0.01882582  0.01760919
head(tx_diversity(iso))
#> # A tibble: 6 × 14
#>   gene_id         gene_name gene_type n_tx_annotated n_tx_assayed n_tx_expressed
#>   <chr>           <chr>     <chr>              <int>        <int>          <int>
#> 1 ENSG0000002319… RNH1      protein_…             24           17             17
#> 2 ENSG0000010042… HDAC10    protein_…             22           16             16
#> 3 ENSG0000022980… XIST      lncRNA                30           18             18
#> 4 ENSG0000007980… DNM2      protein_…             22           15             15
#> 5 ENSG0000007231… SREBF1    protein_…             24           18             18
#> 6 ENSG0000005082… BCAR1     protein_…             22           15             15
#> # ℹ 8 more variables: n_tx_types <int>, tx_types <chr>, mean_gene_expr <dbl>,
#> #   dominant_transcript_id <chr>, dominant_transcript_name <chr>,
#> #   dominant_transcript_type <chr>, dominant_fraction <dbl>,
#> #   effective_isoforms <dbl>
dominant_isoform(iso, group = "condition")
#> # A tibble: 138 × 11
#>    gene_id            gene_name gene_type      condition  dominant_transcript_id
#>    <chr>              <chr>     <chr>          <chr>      <chr>                 
#>  1 ENSG00000009413.16 REV3L     protein_coding preeclamp… ENST00000368802.8     
#>  2 ENSG00000009413.16 REV3L     protein_coding control    ENST00000619481.1     
#>  3 ENSG00000023191.17 RNH1      protein_coding preeclamp… ENST00000356187.9     
#>  4 ENSG00000023191.17 RNH1      protein_coding control    ENST00000397604.7     
#>  5 ENSG00000072310.17 SREBF1    protein_coding preeclamp… ENST00000355815.8     
#>  6 ENSG00000072310.17 SREBF1    protein_coding control    ENST00000261646.10    
#>  7 ENSG00000082996.19 RNF13     protein_coding preeclamp… ENST00000392894.7     
#>  8 ENSG00000082996.19 RNF13     protein_coding control    ENST00000361785.10    
#>  9 ENSG00000100038.19 TOP3B     protein_coding preeclamp… ENST00000444502.5     
#> 10 ENSG00000100038.19 TOP3B     protein_coding control    ENST00000457270.5     
#> # ℹ 128 more rows
#> # ℹ 6 more variables: dominant_transcript_name <chr>,
#> #   dominant_transcript_type <chr>, dominant_is_canonical <lgl>,
#> #   dominant_fraction <dbl>, gene_expr <dbl>, dominant_switch <lgl>
isoform_switches(iso)
#> # A tibble: 34 × 12
#>    gene_id         gene_name gene_type n_tx_tested n_det_sig n_det_up n_det_down
#>    <chr>           <chr>     <chr>           <int>     <int>    <int>      <int>
#>  1 ENSG0000008299… RNF13     protein_…          11         4        1          3
#>  2 ENSG0000008915… GCN1      protein_…           6         4        3          1
#>  3 ENSG0000010056… PSMA3     protein_…           8         3        1          2
#>  4 ENSG0000006366… GPC1      protein_…           6         3        2          1
#>  5 ENSG0000014664… EGFR      protein_…           7         3        3          0
#>  6 ENSG0000004882… FAM120A   protein_…           5         3        3          0
#>  7 ENSG0000008928… FUS       protein_…          11         2        2          0
#>  8 ENSG0000003244… PNPLA6    protein_…          11         2        2          0
#>  9 ENSG0000001134… SYT7      protein_…           7         2        2          0
#> 10 ENSG0000007112… WDR1      protein_…           7         1        1          0
#> # ℹ 24 more rows
#> # ℹ 5 more variables: det_sig_types <chr>, max_abs_log2FC <dbl>,
#> #   gene_log2FC <dbl>, deg_sig <chr>, switch_type <chr>
exon_diversity(iso, gene_name = c("RBPJ", "EGFR"))
#> # A tibble: 2 × 9
#>   gene_id   gene_name gene_type  n_tx mean_exons_per_tx max_exons_per_tx n_exons
#>   <chr>     <chr>     <chr>     <int>             <dbl>            <int>   <int>
#> 1 ENSG0000… RBPJ      protein_…    31              6.52               12      65
#> 2 ENSG0000… EGFR      protein_…    11             14.4                28      46
#> # ℹ 2 more variables: n_constitutive <int>, n_alternative <int>