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Spl-IsoQuant output files

Spl-IsoQuant output files will be stored in <output_dir>, which is set by the user. If the output directory was not specified the files are stored in isoquant_output.

Spl-IsoQuant output is generally controlled by the --analysis option, which can take one or more values from the following list:

  • quantification: reference-based quantification (requires gene annotation);
  • transcript_discovery: discover novel transcript models;
  • exon_quantification: reference-based exon, splice junction, and intron retention counting (requires gene annotation);
  • fusion:fusion gene detection, (requires gene annotation).

Reference-based analysis output

Will be produced only if a reference gene annotation is provided.

Read assignments

  • SAMPLE_ID.read_info.tsv.gz - TSV file with unified per-read information including assignments, exon coordinates, and barcode/UMI data (default output, gzipped by default);
  • SAMPLE_ID.read_assignments.tsv.gz - deprecated TSV file with read to isoform assignments (only with --large_output read_assignments);
  • SAMPLE_ID.corrected_reads.bed.gz - BED file with corrected read alignments (only with --large_output corrected_bed);

Non-grouped counts

Requires --analysis quantification, which will be set by default.

  • SAMPLE_ID.transcript_counts.tsv - TSV file with raw read counts for reference transcript;
  • SAMPLE_ID.gene_counts.tsv - TSV file with raw read counts for reference genes;
  • SAMPLE_ID.transcript_tpm.tsv - TSV file with reference transcript expression in TPM;
  • SAMPLE_ID.gene_tpm.tsv - TSV file with reference gene expression in TPM;

Exon and splice junction counts

If --analysis exon_quantification is set, exon, splice junction and intron retention counts will be produced:

  • SAMPLE_ID.exon_counts.tsv - region-based exon counts: overlapping reference exons are grouped into regions, and each region reports per-variant inclusion counts plus one region-level exclusion count;
  • SAMPLE_ID.exon_splice_site_counts.tsv - exon splice-site counts: per-candidate full / left / right splice-site support and per-region exclusion / ambiguous counts, one row per feature and group;
  • SAMPLE_ID.splice_junction_counts.tsv - reference splice junction inclusion/exclusion read counts (previously named SAMPLE_ID.intron_counts.tsv);
  • SAMPLE_ID.intron_retention_counts.tsv - intron retention event counts per reference intron (same format as splice junction counts);

The old per-exon inclusion/exclusion counts (previous Spl-IsoQuant exon format) are no longer produced by default. Use --old_exon_count_format to additionally output them as SAMPLE_ID.old_exon_counts.tsv (deprecated, will be removed in a future release).

Grouped counts in linear format

Grouped count file names contain the grouping strategy as <strategy> (e.g. file_name, barcode, barcode_spot, or file0_col1 for a file:...:0:1 group). When several --read_group strategies are given, one set of files is produced per strategy.

  • SAMPLE_ID.gene_grouped_<strategy>_counts.linear.tsv
  • SAMPLE_ID.transcript_grouped_<strategy>_counts.linear.tsv
  • SAMPLE_ID.exon_grouped_<strategy>_counts.linear.tsv
  • SAMPLE_ID.exon_splice_site_grouped_<strategy>_counts.linear.tsv
  • SAMPLE_ID.splice_junction_grouped_<strategy>_counts.linear.tsv
  • SAMPLE_ID.intron_retention_grouped_<strategy>_counts.linear.tsv (only with exon quantification)
  • SAMPLE_ID.old_exon_grouped_<strategy>_counts.linear.tsv (only with --old_exon_count_format)

The region-based exon and exon_splice_site grouped counts are produced in linear format only (they are not converted to matrix/MTX format).

The exon splice-site counts carry a group_id column (one row per feature and group; NA when ungrouped). To reconstruct the per-molecule group-list format (one entry per read, e.g. barcodes for downstream cell/cell-type aggregation) use isoquant_lib/scripts/exon_splice_site_to_group_lists.py.

Grouped counts in matrix formats

By default, Spl-IsoQuant converts grouped counts with small number of groups/samples (<=100) to standard matrix format; larger matrices (e.g. for single-cell experiments) will be saved to MTX. Check --counts_format option for details. Linear counts can also be converted to any other format using the script described below.

  • SAMPLE_ID.gene_grouped_<strategy>_counts.tsv - grouped gene counts in standard matrix format;
  • SAMPLE_ID.transcript_grouped_<strategy>_counts.tsv - grouped transcript counts in standard matrix format;
  • SAMPLE_ID.gene_grouped_<strategy>_tpm.tsv - grouped gene TPM values in standard matrix format;
  • SAMPLE_ID.transcript_grouped_<strategy>_tpm.tsv - grouped transcript TPM values in standard matrix format;
  • SAMPLE_ID.splice_junction_grouped_<strategy>_counts.tsv - grouped splice junction counts in standard matrix format; row IDs are chr:start-end:strand, each cell holds include,exclude (comma-separated); produced with exon quantification;
  • SAMPLE_ID.intron_retention_grouped_<strategy>_counts.tsv - grouped intron retention counts in standard matrix format; same layout as splice junction counts; produced with exon quantification;

  • SAMPLE_ID.old_exon_grouped_<strategy>_counts.tsv - grouped legacy per-exon counts in standard matrix format; same layout; only with --old_exon_count_format;

  • SAMPLE_ID.gene_grouped_<strategy>_counts.matrix.mtx, SAMPLE_ID.gene_grouped_<strategy>_counts.features.tsv, SAMPLE_ID.gene_grouped_<strategy>_counts.barcodes.tsv - grouped gene counts in Seurat-compatible MTX format;

  • SAMPLE_ID.transcript_grouped_<strategy>_counts.matrix.mtx, SAMPLE_ID.transcript_grouped_<strategy>_counts.features.tsv, SAMPLE_ID.transcript_grouped_<strategy>_counts.barcodes.tsv - grouped transcript counts in Seurat-compatible MTX format;
  • SAMPLE_ID.gene_grouped_<strategy>_tpm.matrix.mtx, SAMPLE_ID.gene_grouped_<strategy>_tpm.features.tsv, SAMPLE_ID.gene_grouped_<strategy>_tpm.barcodes.tsv - grouped gene TPM values in Seurat-compatible MTX format;
  • SAMPLE_ID.transcript_grouped_<strategy>_tpm.matrix.mtx, SAMPLE_ID.transcript_grouped_<strategy>_tpm.features.tsv, SAMPLE_ID.transcript_grouped_<strategy>_tpm.barcodes.tsv - grouped transcript TPM values in Seurat-compatible MTX format;
  • SAMPLE_ID.splice_junction_grouped_<strategy>_counts.include.matrix.mtx, SAMPLE_ID.splice_junction_grouped_<strategy>_counts.exclude.matrix.mtx, SAMPLE_ID.splice_junction_grouped_<strategy>_counts.features.tsv, SAMPLE_ID.splice_junction_grouped_<strategy>_counts.barcodes.tsv - grouped splice junction counts in Seurat-compatible MTX format; one features file and one barcodes file are shared between the include and exclude matrices; produced with exon quantification;
  • SAMPLE_ID.intron_retention_grouped_<strategy>_counts.include.matrix.mtx, SAMPLE_ID.intron_retention_grouped_<strategy>_counts.exclude.matrix.mtx, SAMPLE_ID.intron_retention_grouped_<strategy>_counts.features.tsv, SAMPLE_ID.intron_retention_grouped_<strategy>_counts.barcodes.tsv - grouped intron retention counts in Seurat-compatible MTX format; produced with exon quantification;
  • SAMPLE_ID.old_exon_grouped_<strategy>_counts.include.matrix.mtx, SAMPLE_ID.old_exon_grouped_<strategy>_counts.exclude.matrix.mtx, SAMPLE_ID.old_exon_grouped_<strategy>_counts.features.tsv, SAMPLE_ID.old_exon_grouped_<strategy>_counts.barcodes.tsv - grouped legacy per-exon counts in Seurat-compatible MTX format; only with --old_exon_count_format;

Note that grouped counts can be converted to any format using /isoquant_lib/quantification/convert_grouped_counts.py. The script accepts the following arguments:

--output or -o Output prefix name;

--input or -i Path to counts files in linear Spl-IsoQuant format;

--genedb or -g Gene annotation in gffutils .db format (can be found in Spl-IsoQuant log), feature names will be used instead of IDs if provided; works only for genes and transcripts;

--feature_type {gene,transcript,exon,intron} Feature type to be converted [gene, transcript, exon, intron]; annotation lookup applies only to genes/transcripts;

--output_format {mtx,matrix} or -f {mtx,matrix} Output format; matrix is a simple TSV matrix (not recommended for large matrices), mtx is a Seurat-compatible MTX format; --tpm Convert counts to TPM (works only for genes and transcripts);

--gzip Gzip output files.

Combined counts

If multiple experiments are provided, aggregated expression matrices will be placed in <output_dir>:

  • combined_gene_counts.tsv
  • combined_gene_tpm.tsv
  • combined_transcript_counts.tsv
  • combined_transcript_tpm.tsv

PolyA / TSS site prediction

Whenever a gene annotation is provided, Spl-IsoQuant predicts known and novel polyA sites:

  • SAMPLE_ID.polyA_prediction.tsv - predicted polyA sites per reference transcript.

If --fl_data is also supplied (reads represent full-length transcripts), the same machinery is applied to read start positions:

  • SAMPLE_ID.TSS_prediction.tsv - predicted transcription start sites per reference transcript.

If --read_group is set, per group polyA/TSS counts will also be computed:

  • SAMPLE_ID.polyA_prediction_grouped_<strategy>
  • SAMPLE_ID.TSS_prediction_grouped_<strategy> (only with --fl_data)

Transcript discovery output

Produced only when transcript_discovery is among the requested --analysis values. Enabled by default with gene annotation in bulk mode and in annotation-free mode.

  • SAMPLE_ID.transcript_models.gtf - GTF file with discovered expressed transcript (both known and novel transcripts);
  • SAMPLE_ID.transcript_model_reads.tsv.gz - which reads contributed to which transcript models, in the same unified read_info format as SAMPLE_ID.read_info.tsv (gzipped by default);
  • SAMPLE_ID.extended_annotation.gtf - GTF file with the entire reference annotation plus all discovered novel transcripts;

Counts (based on SAMPLE_ID.transcript_models.gtf):

  • SAMPLE_ID.discovered_transcript_counts.tsv - raw read counts for discovered transcript models (corresponds to SAMPLE_ID.transcript_models.gtf);
  • SAMPLE_ID.discovered_gene_counts.tsv - raw read counts for discovered genes (corresponds to SAMPLE_ID.transcript_models.gtf);
  • SAMPLE_ID.discovered_transcript_tpm.tsv - expression of discovered transcripts models in TPM (corresponds to SAMPLE_ID.transcript_models.gtf);
  • SAMPLE_ID.discovered_gene_tpm.tsv - expression of discovered genes in TPM (corresponds to SAMPLE_ID.transcript_models.gtf);

If --read_group is set, the per-group counts will be also computed:

  • SAMPLE_ID.discovered_transcript_grouped_<strategy>_counts.linear.tsv
  • SAMPLE_ID.discovered_gene_grouped_<strategy>_counts.linear.tsv

Similarly to the reference-based counts, these counts are converted to other formats as described above.

If --sqanti_output is set, Spl-IsoQuant will produce output in SQANTI-like format:

  • SAMPLE_ID.novel_vs_known.SQANTI-like.tsv - discovered novel transcripts vs reference transcripts (similar, but not identical to SQANTI classification.txt);

Fusion detection output

Produced only when fusion is among the requested --analysis values.

Fusion detection runs after the isoform pipeline and reports candidate gene fusions:

  • fusion_<bam_basename>.tsv - detected gene fusions, one file per input BAM, placed directly in <output_dir>;

See output formats for a description of the columns.

Output for single-cell and spatial modes

By default, in single-cell and spatial modes Spl-IsoQuant only performs quantification analysis.

UMI-filtered reads will be saved to the same read_info format. All counts formats will also be identical (see above).

If Spl-IsoQuant detects the barcodes, barcoded reads will be saved in TSV format. If barcode calling also splits the reads into individual cDNAs, a FASTA file with cDNAs will be produced.

Note that transcript discovery is performed only in bulk mode by default. Single-cell and spatial modes require UMI deduplication. Reads that are not assigned to any gene are discarded. Hence, novel gene discovery will not be performed in single-cell/spatial mode. We recommend using bulk mode for novel gene and transcript discovery.

Full documentation for single-cell and spatial modes.

Other files

Additionally, an isoquant.log log file will be saved to the output directory.

If raw reads were provided, BAM file(s) will be stored in <output_dir>/<SAMPLE_ID>/aux/.
In case --keep_tmp option was specified this directory will also contain temporary files.