GenomeTrackBinnedTransform.cpp by avoiding arithmetic
between distinct anonymous enum types.gdb.export_fasta() to export all contigs from a
database to a multi-FASTA file, defaulting to the current gdb with
optional groot override.gscreen and
gextract with dense iterators.lse virtual track function that computes the
log-sum-exp of the values in the iterator interval.gsetroot() for your primary writable database, then
gdataset.load() to add read-only datasetsforce=TRUE
to override (working db always wins)gdataset.load(): Load a dataset into the namespace
(tracks and intervals become available)gdataset.unload(): Remove a dataset from the
namespacegdataset.save(): Create a new dataset from selected
tracks/intervalsgdataset.ls(): List working database and all loaded
datasetsgdataset.info(): Show metadata and contents of a
datasetgtrack.dataset(): Get the source path for a track
(working db or dataset)gtrack.dbs(): Get all paths where a track exists (for
debugging shadowed tracks)gintervals.dataset(): Get the source path for an
interval setgintervals.dbs(): Get all paths where an interval set
existsdb parameter for filtering by source:
gtrack.ls(db = "/path/to/dataset"): List tracks from a
specific sourcegintervals.ls(db = "/path/to/dataset"): List intervals
from a specific sourcechrom_sizes.txt files
(same genome assembly)gsetroot() works unchangedgtrack.mv(): Rename or move a track within the same
databasegtrack.copy(): Copy a track (can copy between databases
when multiple are loaded)gcor function that computes correlation between
two tracks, or between multiple pairs of tracks.gextract and gscreen almost always
did not enable multitasking mode due to incorrect gating.dataframe and names parameters to
gdist function that return a data frame instead of an
N-dimensional vector.gsynth.train, gsynth.sample and
gsynth.save functions that train a Markov model from a
genome sequence and sample a synthetic genome from the modelgseq.kmer.dist function that counts the number of
occurrences of k-mers in genomic intervals.gtrack.liftover that created overlapping
intervals when lifting sparse tracks.gintervals.normalize.gintervals.normalize now
returns +1bp for intervals with odd sizes:
interval_relative parameter to
giterator.intervals() for interval-aligned bin
iteration.genome.seq +
genome.idx files instead of per-chromosome filesgdb.info(),
gdb.convert_to_indexed(),
gtrack.convert_to_indexed(),
gintervals.convert_to_indexed(),
gintervals.2d.convert_to_indexed()options(gmulticontig.indexed_format = FALSE) to
create databases in legacy format for compatibility with older misha
versionsvignette("Database-Formats") for more details.gmax.processes automatically set to 70% of available
CPU coresgmax.data.size coordinated with process limits to
ensure total memory usage <= 70% of RAM (capped at 10GB per
process)gmax.data.size = min((RAM * 0.7) / gmax.processes, 10GB)
ensures safe memory usage across all parallel processesgmax.processes * 1000 records (e.g., 2K on laptops, 89K on
128-core servers)options()vignette("Manual")
for detailsgvtrack.create with src parameter). These
tracks behave exactly like regular sparse tracks, but are stored in
memory and can be used in track expressions.sshift, eshift and
filter parameters to gvtrack.create.gintervals.path() and gtrack.path()
functions that return the actual file system paths for interval sets and
tracks.masked.count and masked.frac virtual
track functions that count and fraction masked base pairs (lowercase
letters) in the current iterator interval.distance.edge virtual track function that
computes edge-to-edge distance from the iterator interval to the closest
source interval, using the same calculation as
gintervals.neighbors.gtrack.liftover did not fill chromosomes missing
the chain with NA values. This caused errors when trying to access the
tracks afterwards.gintervals.as_chain function that converts a data
frame to a chain object.gintervals.liftover via value_col and
multi_target_agg parameters.src_overlap_policy and
tgt_overlap_policy parameters to
gintervals.liftover, gintervals.load_chain,
and gtrack.liftover functions.gtrack.liftover via
multi_target_agg parameter.gintervals.load_chain now returns valid misha intervals
instead of a chain object.gintervals.load_chain now includes score
and chain_id columns for all loaded chainsmin_score parameter in
gintervals.load_chain, gintervals.liftover,
and gtrack.liftover filters out low-quality chainstgt_overlap_policy = "auto_score" (or
"auto") selects the best chain mapping based on alignment
score (highest score → longest span → lowest chain_id)include_metadata parameter in
gintervals.liftover optionally returns score and chain_id
for each mapping BREAKING: “auto” is now an alias for
“auto_score”. For the old behavior, use
tgt_overlap_policy = "auto_first".canonic parameter to
gintervals.liftover (default FALSE) to merge
adjacent target intervals resulting from the same source interval and
chain.tgt_overlap_policy = "best_cluster_union" (default,
aliased as "best_source_cluster"): Uses source union
coveragetgt_overlap_policy = "best_cluster_sum": Uses sum of
target lengthstgt_overlap_policy = "best_cluster_max": Uses longest
single membermax.pos.abs, max.pos.relative,
min.pos.abs, min.pos.relative: Returns the
position of the maximum/minimum value in the iterator intervalexists: Returns 1 if any value exists (or specific vals
if provided), 0 otherwisesize: Returns the number of non-NaN values in the
iterator intervalsample: Returns a uniformly sampled source value from
the iterator intervalsample.pos.abs and sample.pos.relative:
Returns the position of a uniformly sampled valuefirst and last: Returns the first/last
value in the iterator intervalfirst.pos.abs, first.pos.relative,
last.pos.abs, last.pos.relative: Returns the
position of the first/last valuegintervals.neighbors when using
mindist=0, maxdist=0: the function would miss zero-distance
(touching) intervals when using mindist=0, maxdist=0.pwm.count with spatial sliding windows
double-counting bidirectional hits (forward + reverse) at the same
genomic position; the sliding path now matches the baseline per-position
union semantics.gintervals.load_chain now
returns a data frame with 8 columns instead of 7. Columns are:
chrom, start, end,
strand, chromsrc, startsrc,
endsrc, strandsrc.src_overlap_policy and
tgt_overlap_policy parameters to
gintervals.load_chain, gtrack.liftover and
gintervals.liftover functions.neighbor.count virtual track.gintervals.mark_overlaps function that marks
overlapping intervals with a group ID.pssm parameter of
gvtrack.create and gseq.pwm functions.gseq.pwm and added
neutral_chars_policy parameter.pwm, pwm.max and pwm.count) for
dense iterators when spatial weighting is disabled, providing
significant performance improvements for consecutive genomic
intervals.pwm.count(bidirect=TRUE) now
counts per-position union of strands (via log-sum-exp),
aligning with pwm/pwm.max. Each position
contributes at most 1 to the count. To reproduce the old per-strand-sum
behavior, add the two strand-specific counts:
pwm.count(bidirect=FALSE, strand=1) + pwm.count(bidirect=FALSE, strand=-1).gseq.pwm and gseq.kmer functions
that compute pwm and kmer scores on sequences without the need for a
genome database.gseq.rev and gseq.comp functions
that reverse and complement DNA sequences without the need for a genome
database.gseq.revcomp alias for grevcomp
function.gintervals.random function that generates random
genome intervals.gintervals.covered_bp and
gintervals.coverage_fraction functions that calculate the
number of base pairs and the fraction of base pairs covered by a set of
intervals.gvtrack.filters: per vtrack genomic masks.pwm.count virtual track function that counts the
number of occurrences of a PWM in the current iterator interval.gintervals.neighbors.upstream() - Find upstream
neighbors relative to query strandgintervals.neighbors.downstream() - Find downstream
neighbors relative to query strandgintervals.neighbors.directional() - Find both upstream
and downstream neighborsuse_intervals1_strand parameter to
gintervals.neighbors() to use query intervals’ strand for
distance directionality.warn.ignored.strand parameter to
gintervals.neighbors() to control warnings when query
strand is ignored.gintervals.neighbors: a stack imbalance
in the C++ code in very rare cases of 2D intervals.gintervals.neighbors due to unbalanced
rprotect calls.gintervals.normalize and
gintervals.annotate functions.m1-asan build.pwm and kmer virtual track
functions: iterator shifts were not applied.colnames parameter to
gintervals.mapply function.attrs parameter to gtrack.import
function.created.user default attribute in track creation
functions.gtrack.import function.gtrack.create_dense function - creates a dense
track from an intervals and values.clock_gettime is missing).gtrack.import_bigwig:
intern argument was not passed to system
calls.grevcomp function (reverse complement of a DNA
sequence).gvtrack.create.gdb.create_genome function.R_curErrorBuf,
SET_TYPEOFRf_
prefix in the c++ code.gtrack.import from bigwig.ALLGENOME is now only soft deprecated in order to
support old misha scripts.gtrack.create_dirs function.gcluster.run.gintervals.neighbors..misha. Variables such as
ALLGENOME can now be accessed as
.misha$ALLGENOME. This change is not backwards compatible,
please update your code accordingly.gintervals.neighbors (same as
gintervals.neighbors1 from misha.ext). This
means that instead of having two columns of ‘chrom’, ‘start’ and ‘end’,
the resulting data frame would have ‘chrom1’, ‘start1’ and ‘end1’.gwget now uses curl in order to work on
systems that do not have ftp installed.markdown format.Genomes vignette that demonstrates how to
create a new genome database.
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