The hardware and bandwidth for this mirror is donated by METANET, the Webhosting and Full Service-Cloud Provider.
If you wish to report a bug, or if you are interested in having us mirror your free-software or open-source project, please feel free to contact us at mirror[@]metanet.ch.
no visible binding for '..keep' NOTE in
.gene_exons(): replaced exons[, ..keep] with
exons[, keep, with = FALSE].no visible binding for 'x' NOTE in
.build_plot(): added x to
globalVariables() in globals.R.get_pseudo_correlation() example in
\donttest{} to avoid exceeding the CRAN 5-second example
time limit.plot_exclusive_junctions() and
plot_exclusive_junctions_event() now accept RefSeq-style
GTFs that lack gene_name / transcript_name
attributes. The internal attribute extractor tries
gene_name -> gene_id ->
gene, and transcript_name ->
transcript_id, so a RefSeq annotation like NCBI’s
GCF_*_GRCh38 file works with no manual preprocessing.splikit_junction_plot with
components $plot (ggplot), $info (tidy
per-junction data.table), plus the underlying exons /
junctions / tx_order tables. The
info data.table includes gene_name,
gene_id, transcript_name,
transcript_id, chr, strand,
j_start, j_end, j_width,
exclusive, n_tx_with_junction,
observed_in_eventdata, row_names_mtx, and
is_annot for straightforward downstream analysis.print() method for the new class:
rendering the plot and printing info when the object is
auto-printed at the REPL..gtf_attr,
.load_gene_gtf, .gene_exons,
.tx_junctions, .order_transcripts,
.build_plot, .build_info) so the GTF-only and
eventdata-based plots now share a single implementation path.print(summary_table) calls in
make_junction_ab(), make_gene_count(), and
make_velo_count() with
message(paste(capture.output(...), collapse = "\n")). The
summary now respects suppressMessages() and stays behind
the verbose = TRUE guard. A stray
if (verbose) cat(...) in make_m1() was
likewise converted to message() for consistency.plot_exclusive_junctions_event() -
sibling of plot_exclusive_junctions() that sources the
drawn arcs from a splikit eventdata table. Exon structure
still comes from the GTF and exclusivity is computed gene-wide from the
annotation, but only junctions whose (i.start, i.end)
coordinates are observed in eventdata are drawn. If
eventdata lacks a gene_name column the
function runs make_eventdata_plus() internally using the
supplied GTF path. The plot is rendered directly to the current graphics
device (no out_file).plot_exclusive_junctions() renders a gene model with
one row per transcript, exon rectangles, intron/junction arcs, and
Ensembl ids shown beneath transcript names on the y-axis. Junctions used
by a single transcript of the gene are highlighted as solid black arcs;
shared junctions render as thin grey arcs.show_exclusive (restrict to exclusive-owning
transcripts), transcript (pin the plot to one or more
transcript names), curvature (arc-height knob).plot_exclusive_junctions_pdf() writes a multi-page PDF:
page 1 is the full gene view, subsequent pages show each exclusive
transcript with its exclusive junction in black.data.table.
ggplot2 is declared under Suggests.make_eventdata_plus() gene_name
extraction
sub('.*gene_name "([^"]+)".*', ...), which returns the
input unchanged when no match is found. Gene records without a
gene_name attribute (e.g. ~310 rows in Ensembl mouse
GRCm39.110) therefore ended up with a gene_name equal to
the full attribute blob.grepl()-guarded extractor that returns
NA on no-match, with a fallback to gene_id so
downstream matching by name keeps working. The function now emits a
message() reporting how many records required the
fallback.find_variable_genes() now supports
n_threads parameter for faster computation with
method = "sum_deviance"make_m2() now includes automatic detection of memory
limitsbatch_size,
memory_threshold, force_fast for fine-tuned
controlget_pseudo_correlation() now supports both Cox-Snell
and Nagelkerke R² metricsmetric parameter for selecting correlation type
(default: “CoxSnell”)make_junction_ab() enhanced with:
verbose parameter for detailed progress trackingkeep_multi_mapped_junctions option for including
multi-mapped readsmake_m1() now includes:
min_counts parameter for filtering low-count
eventsverbose option for progress monitoringmake_m2()verbose = FALSE for
critical stepsmultithread →
multi_thread)None - all changes are backward compatible. Existing code will continue to work with default parameters.
This release includes contributions addressing issue #16, focusing on performance enhancements and multi-threading support. Special thanks to all users who provided feedback and testing.
# Install from GitHub
devtools::install_github("Arshammik/splikit")
# Load the package
library(splikit)For questions or issues, please visit: https://github.com/Arshammik/splikit/issues
These binaries (installable software) and packages are in development.
They may not be fully stable and should be used with caution. We make no claims about them.