Parallelization(basic support complete. See below)
- Native python library (re-using C++ backend)
- Peak-gene correlations
- MACS peak calling
Contributions welcome :)
svds()function, based on the excellent Spectra C++ library (used in RSpectra) by Yixuan Qiu. This should ensure lower memory usage compared to
irlba, while achieving similar speed + accuracy.
- Limited parallelization is now supported. This is easiest to use via the
- Reading text-based MatrixMarket inputs (e.g. from 10x or Parse) is now supported via
import_matrix_market()and the convenience function
import_matrix_market_10x(). Our implementation uses disk-backed sorting to allow importing large files with low memory usage.
binarize()function and associated generics
>=. This only supports comparison with non-negative numbers currently. (Thanks to contribution from @brgew)
round()matrix transformation (Thanks to contributions from @brgew)
- Add getter/setter function
all_matrix_inputs()to help enable relocating the underlying storage for BPCells matrix transform objects.
- All hdf5-writing functions now support a
gzip_levelparameter, which will enable a shuffle + gzip filter for compression. This is generally much slower than bitpacking compression, but it adds improved storage options for files that must be read by outside programs. Thanks to @ycli1995 for submitting this improvement in pull #42.
- AnnData export now supported via
- Re-licensed code base to use dual-licensed Apache V2 or MIT instead of GPLv3
- Merging fragments with
c()now handles inputs with mismatched chromosome names.
- Merging fragments is now 2-3.5x faster
- SNN graph construction in
knn_to_snn_graph()should work more smoothly on large datasets due to C++ implementation
- Reduced memory usage in
marker_features()for samples with millions of cells and a large number of clusters to compare.
- On Windows, increased the maximum number of files that can be simultaneously open. Previously, opening >63 compressed counts matrices simultaneously would hit the limit. Now at least 1,000 simultaneous matrices should be possible.
- Subsetting peak or tile matrices with
[now propagates through so we always avoid computing parts of the peak/tile matrix that have been discarded by our subset. Subsetting a tile matrix will automatically convert into a peak matrix when possible for improved efficiency.
- Subsetting RowBindMatrices now propagates through so we avoid touching matrices with no selected indices
- Additional C++17 filesystem backwards compatibility that should allow slightly older compilers such as GCC 7.5 to build BPCells.
- Fixed a few fragment transforms where using
chrNames(frags) <- valor
cellNames(frags) <- valcould cause downstream errors.
- Fixed errors in
transpose_storage_order()for matrices with >4 billion non-zero entries.
- Fixed error in
transpose_storage_order()for matrices with no non-zero entries.
- Fixed bug writing fragment files with >512 chromosomes.
- Fixed bug when reading fragment files with >4 billion fragments.
- Fixed file permissions errors when using read-only hdf5 files (Issue #26 reported thanks to @ttumkaya)
colnames()is now propagated when saving matrices (Issue #29 reported thanks to @realzehuali, with an additional fix after report thanks to @Dario-Rocha)
- Fixed 64-bit integer overflow (!) that could cause incorrect p-value calculations in
marker_features()for features with more than 2.6 million zeros.
- Improved robustness of the Windows installation process for setups that do not need the -lsz linker flag to compile hdf5
- Fixed possible memory safety bug where wrapped R objects (such as dgCMatrix) could be potentially garbage collected while C++ was still trying to access the data in rare circumstances.
- Fixed case when dimnames were not preserved when calling
convert_matrix_type()twice in a row such that it cancels out (e.g. double -> uint32_t -> double). Thanks to @brgrew reporting issue #43
- Caused and fixed issue resulting in unusably slow performance reading matrices from HDF5 files. Broken versions range from commit 21f8dcf until the fix in 3711a40 (October 18-November 3, 2023). Thanks to @abhiachoudhary for reporting this in issue #53
- Fixed error with
svds()not handling row-major matrices correctly. Thanks to @ycli1995 for reporting this in issue #55
- ATAC-seq Analysis
- Reading/writing 10x fragment files on disk
- Reading/writing compressed fragments on disk (in folder or hdf5 group)
- Interconversion of fragments objects with GRanges / data.frame
- Merging of multiple source fragment files transparently at run time
- Calculation of Cell x Peak matrices, and Cell x Tile matrices
- ArchR-compatible QC calculations
- ArchR-compatible gene activity score calculations
- Filtering fragments by chromosmes, cells, lengths, or genomic region
- Fast peak calling approximation via overlapping tiles
- Single cell matrices
- Conversion to/from R sparse matrices
- Read-write access to 10x hdf5 feature matrices, and read-only access to AnnData files
- Reading/writing of compressed matrices on disk (in folder or hdf5 group)
- Support for integer or single/double-precision floating point matrices on disk
- Fast transposition of storage order, to switch between indexing by cell or by gene/feature.
- Concatenation of multiple source matrix files transparently at run time
- Single-pass calculation of row/column mean and variance
- Wilcoxon marker feature calculation
- Transparent handling of vector
log1pfor streaming normalization, along with other less common operations. This allows implementation of ATAC-seq LSI and Seurat default normalization, along with most published log-based normalizations.
- SCTransform pearson residual calculation
- Multiplication of sparse matrices
- Single cell plotting utilities
- Read count knee cutoffs
- UMAP embeddings
- Dot plots
- Transcription factor footprinting / TSS profile plotting
- Fragments vs. TSS Enrichment ATAC-seq QC plot
- Pseudobulk genome track plots, with gene annotation plots
- Additional utility functions
- Matching gene symbols/IDs to canonical symbols
- Download transcript annotations from Gencode or GTF files
- Download + parse UCSC chromosome sizes
- Parse peak files BED format; Download ENCODE blacklist region
- Wrappers for knn graph calculation + clustering
Note: All operations interoperate with all storage formats. For example, all matrix operations can be applied directly to an AnnData or 10x matrix file. In many cases the bitpacking-compressed formats will provide performance/space advantages, but are not required to use the computations.