Results table of xtail results — xtail-accessors • xtail

To retrieve the results from the xtail run use one of the accessor functions.

# S4 method for xtail
conditions(object)

resultsNum(object, ...)

# S4 method for xtail
resultsNum(object, ...)

resultsTable(object, ...)

# S4 method for xtail
resultsTable(object, sort.by = NULL, log2FCs = FALSE, log2Rs = FALSE, ...)

summary(object, ...)

# S3 method for xtail
summary(object, alpha = 0.1, ...)

Arguments

object	a `xtail` object
...	optional arguments. Currently not used
sort.by	the column to sort with. Defaults to `NULL` to disable sorting.
log2FCs	`TRUE` or `FALSE`: Should log2 fold change values be returned? (defaults to `TRUE`)
log2Rs	`TRUE` or `FALSE`: Should log2 ratio values be returned? (defaults to `TRUE`)
alpha	cut off for summarizing results. Only results with a adjusted p-value lower than `alpha` will be reported.

Value

a DataFrame with the results or numeric vectors

Examples

data(xtailres)
resultsTable(xtailres)
#> DataFrame with 11391 rows and 8 columns
#>                 log2FC_TE_v1 pvalue_v1 treat_log2TE log2FC_TE_v2 pvalue_v2
#>                    <numeric> <numeric>    <numeric>    <numeric> <numeric>
#> ENSG00000000003    0.0586807  0.816556    0.5525063    0.0606827  0.809767
#> ENSG00000000419    0.3559950  0.156433    1.3654645    0.3559950  0.142658
#> ENSG00000000457   -0.2993342  0.590709   -0.0608568   -0.2961310  0.644911
#> ENSG00000000460   -0.3108003  0.422875    0.8068549   -0.3109200  0.429114
#> ENSG00000000971   -0.6223233  0.710533    1.2996842   -0.6457720  0.744394
#> ...                      ...       ...          ...          ...       ...
#> ENSG00000269554    -1.350446  0.368365    -1.043198    -1.319616  0.465733
#> ENSG00000269858    -0.438702  0.395772    -0.112495    -0.433296  0.441749
#> ENSG00000271303     0.196158  0.727864     1.319120     0.211647  0.662602
#> ENSG00000272047     0.380683  0.337756    -0.114807     0.387489  0.385950
#> ENSG00000272325     0.748690  0.199407    -4.520208     0.777519  0.379993
#>                 log2FC_TE_final pvalue_final pvalue.adjust
#>                       <numeric>    <numeric>     <numeric>
#> ENSG00000000003       0.0586807     0.816556      0.995279
#> ENSG00000000419       0.3559950     0.156433      0.995279
#> ENSG00000000457      -0.2961310     0.644911      0.995279
#> ENSG00000000460      -0.3109200     0.429114      0.995279
#> ENSG00000000971      -0.6457720     0.744394      0.995279
#> ...                         ...          ...           ...
#> ENSG00000269554       -1.319616     0.465733      0.995279
#> ENSG00000269858       -0.433296     0.441749      0.995279
#> ENSG00000271303        0.196158     0.727864      0.995279
#> ENSG00000272047        0.387489     0.385950      0.995279
#> ENSG00000272325        0.777519     0.379993      0.995279
conditions(xtailres)
#> [1] "control" "treat"  
resultsNum(xtailres)
#> numFoldChange      numRatio 
#>          2033          9358 

# sorting or results
resultsTable(xtailres, sort.by = "pvalue.adjust")
#> DataFrame with 11391 rows and 8 columns
#>                 log2FC_TE_v1   pvalue_v1 treat_log2TE log2FC_TE_v2   pvalue_v2
#>                    <numeric>   <numeric>    <numeric>    <numeric>   <numeric>
#> ENSG00000167658     -2.73757 3.70121e-22     -2.19604     -2.73360 1.57571e-20
#> ENSG00000169100     -2.18854 5.72333e-15     -2.39282     -2.18854 5.47094e-15
#> ENSG00000170275     -2.19020 2.43053e-15     -2.69365     -2.19107 2.98390e-14
#> ENSG00000108107     -1.88774 2.59789e-12     -1.71764     -1.88752 4.31853e-11
#> ENSG00000104529     -1.74938 8.30789e-12     -1.69841     -1.74524 7.70373e-11
#> ...                      ...         ...          ...          ...         ...
#> ENSG00000108469     0.000000    0.999090     0.179843    0.0000000    0.986644
#> ENSG00000132824     0.000000    0.999182     0.196572    0.0000000    0.990604
#> ENSG00000117877     0.000000    0.999422     0.752869    0.0000000    0.992684
#> ENSG00000112877     0.000000    0.999588     0.217930    0.0000000    0.988902
#> ENSG00000177464     0.054963    0.999724    -2.134134    0.0714875    0.914835
#>                 log2FC_TE_final pvalue_final pvalue.adjust
#>                       <numeric>    <numeric>     <numeric>
#> ENSG00000167658        -2.73360  1.57571e-20   1.79490e-16
#> ENSG00000169100        -2.18854  5.72333e-15   3.25972e-11
#> ENSG00000170275        -2.19107  2.98390e-14   1.13299e-10
#> ENSG00000108107        -1.88752  4.31853e-11   1.22981e-07
#> ENSG00000104529        -1.74524  7.70373e-11   1.75506e-07
#> ...                         ...          ...           ...
#> ENSG00000108469        0.000000     0.999090      0.999441
#> ENSG00000132824        0.000000     0.999182      0.999446
#> ENSG00000117877        0.000000     0.999422      0.999598
#> ENSG00000112877        0.000000     0.999588      0.999676
#> ENSG00000177464        0.054963     0.999724      0.999724