IsoQuant 3.13.0

• Improved recall for 10x single-cell barcode calling;

• Added cDNA splitting mode for 10x barcode calling;

• Improved exon and splice junction counts output (TSV matrix and mtx format);

• Added no_auto read grouping mode to avoid automatic grouping.

IsoQuant 3.12.2

Fix package naming.

IsoQuant 3.12.1

Add pip installation.

IsoQuant 3.12.0

• TSV output files do not have a # in headers for easier downstream processing (thanks to @yinshiyi).

• Fix Python 3.14 compatibility.

• Add --barcoded_bam flag for reading barcodes and UMIs directly from a input BAM.

• Add --barcode2barcode option for Visium HD data processing.

• Dramatic speed-up for 10x and universal barcode calling on large whitelists.

• Per-barcode counts grouping is now performed automatically if the barcodes are set.

IsoQuant 3.11.1

• Fix Python 3.8

• Fix MTX conversion.

IsoQuant 3.11.0

• --read_group now supports multiple read grouping strategies. You can now simultaneously group counts by samples, BAM tags, read attributes provided in separate TSV files or within read ids themselves.

• New --large_output option to control which large output files are generated.

• Significant performance optimizations.

• Experimental release of the single-cell/spatial IsoQuant pipeline. Official release will follow soon.

IsoQuant 3.10.0

• New --unmapped_bam option for providing unmapped BAM files typical for PacBio CCS data.

• New --polya_trimmed option to indicate polyA-trimmed reads (thanks @hmutpw for the suggestion #342).

• New --process_only_chr option to process a specific list of chromosomes.

IsoQuant 3.9.0

• Secondary alignments are not used by default from now on. It significantly improves running time and RAM consumption, but barely affects the results' quality.
  Use --use_secondary to process secondary alignments.

• New options that force IsoQuant to use only a faction of reads in high-coverage loci.
  Significantly improves running time and RAM consumption, but affects gene/isoform counts.
  New default behavior only affects small chromosomes and scaffolds (<500kbp).

  In some cases, high-coverage regions take too much time to process due to extreme number of mapped reads,
  especially chrM (up to 10x longer compared to normal chromosomes). However, using only a fraction of these
  reads is enough to obtain reliable results.

  These options allow to process only up to given number of reads mapping to a high-coverage loci on short and normal chromosomes:

  • --max_coverage_small_chr (default value is 1 million);
  • --max_coverage_normal_chr (default value is infinity, so usual chromosomes are not affected by default even if some genes have extreme coverage).

• New option --discard_chr to discard a list chromosomes from the analysis.

IsoQuant 3.8.0

• Fixed --report_canonical preset (#332, thanks to @wwliao).
• Fixed counts for novel genes in discovered_gene_counts.tsv and discovered_gene_tpm.tsv (#337, thanks to @yjliuhub).
• Fixed --genedb_output option (#335, thanks to @YalanBi).

IsoQuant 3.7.1

• Support for indexing BAMs with large chromosomes, fixes #327. Thanks to @maol-corteva.
• CDS features are now used when exon features are absent, fixes #309.
• Chromosome names are now checked for consistency between reference genome, annotation and BAM file provided. Only overlapping chromosome names are used if inconsistent.
• Fixed SQANTI-like output headers, fixes #318.
• Some minor cosmetics.