Changes

v0.15 (2022-04-07)

  • Change the algorithm used for describing how the discovered V gene differs from the germline gene (the database_changes column). This gives more sensible descriptions when the V gene is truncated at one end.

  • Faster startup time (mostly noticable when using --version or --help)

  • Ensure candidates get a unique name even if the hashes (_Sxxxx) collide

  • #108 Print a sensible error message when the GUI cannot be started.

v0.14 (2022-03-10)

  • Fix a crash (KeyError) during “igdiscover augment” when region info for a database sequence could not be obtained.

v0.13 (2022-02-21)

  • IgDiscover now uses AIRR-formatted files: See the AIRR rearrangement schema

  • IgBLAST is run with the appropriate parameters to produce AIRR-compliant files

  • assigned.tab.gz and filtered.tab.gz contain this IgBLAST output plus extra columns that IgDiscover needs (the AIRR schema allows extra columns)

*assigned.tab.gz and filtered.tab.gz are now called assigned.tsv.gz and

filtered.tsv.gz (the .tsv extension is required by the AIRR specification)

  • One downside is that, because there are more columns than before, the “assigned” and “filtered” files are larger than before.

  • The upside is that these files can be used with other tools that accept AIRR-compliant files.

  • Old “assigned” and “filtered” files can still be read by most IgDiscover commands. Output will always use new column names.

  • The VDJ_nt column was removed to reduce file size somewhat. It is now recomputed when necessary from the appropriate offsets.

  • Update to IgBLAST 1.17

v0.12 (2020-01-20)

  • The discoverj command was renamed to discoverjd to reflect that it also supports D gene discovery.

  • Previously, the why_filtered column would show a generic is_duplicate reason for filters that compare candidates to each other. Now each filter criterion can be distinguised.

  • The somewhat vague “too similar sequence” germline filter criterion incorrectly removed some candidates that have a mutation close to the 3’ end. This was replaced with a simpler filter that only ensures that there are no two candidates with the same sequence.

  • Use IgBLAST 1.10

  • Get rid of some unnecessary dependencies by no longer requiring the unmaintained sqt library. Installation with Conda is now faster and requires half the disk space.

  • Add a full_exact column to candidates.tab

v0.11 (2018-11-27)

  • The IgBLAST cache is now disabled by default. We assume that, in most cases, datasets will not be re-run with the exact same parameters, and then it only fills up the disk. Delete your cache with rm -r ~/.cache/igdiscover to reclaim the space. To enable the cache, create a file ~/.config/igdiscover.conf with the contents use_cache: true.

  • If you choose to enable the cache, results from the PEAR merging step will now also be cached. See also the caching documentation.

  • Added detection of chimeras to the (pre-)germline filters. Any novel allele that can be explained as a chimera of two unmodified reference alleles is marked in the new_V_germline.tab file. This is a bit sensitive, so the candidate is currently not discarded.

  • Two additional files annotated_V_germline.tab and annotated_V_pregermline.tab are created in each iteration during the germline filtering step. These are identical to the candidates.tab file, except that they contain a why_filtered column that describes why a sequence was filtered. See the documentation for this feature.

  • A more realistic test dataset (v0.5), now based on human instead of rhesus data, was prepared. The testing instructions have been updated accordingly.

  • J discovery has been tuned to give fewer truncated sequences.

  • Statistics are written to stats/stats.json.

  • V SHM distribution plots are created automatically and written written to v-shm-distributions.pdf in each iteration folder.

  • An igdiscover dbdiff subcommand was added that can compare two FASTA files.

v0.10 (2018-05-11)

  • When computing a consensus sequence, allow some sequences to be truncated in the 3’ end. Many of the discovered novel V alleles were truncated by one nucleotide in the 3’ end because IgBLAST does not always extend the alignment to the end of the V sequence. If these slightly too short V sequences were in the majority, their consensus would lead to a truncated sequence as well. The new consensus algorithm allows for this effect at the 3’ end and can therefore more often than previously find the full sequence. Example:

    TACTGTGCGAGAGA (seq 1)
TACTGTGCGAGAGA (seq 2)
TACTGTGCGAGAG- (seq 3)
TACTGTGCGAG--- (seq 4)
TACTGTGCGAG--- (seq 5)

TACTGTGCGAGAG  (previous consensus)
TACTGTGCGAGAGA (new consensus)

  • Add a column database_changes to the new_V_germline.tab file that describes how the novel sequence differs from the database sequence. Example: 93C>T; 114A>G

  • Allow filtering by CDR3_shared_ratio and do so by default (needs documentation)

  • Cache the edit distance when computing the distance matrix. Speeds up the discover command slightly.

  • discover: Use more than six CPU cores if available

  • igblast: Print progress every minute

v0.9 (2018-03-22)

  • Implemented allele ratio filtering for J gene discovery

  • J genes are discovered as part of the pipeline (previously, one needed to run the discoverj script manually)

  • In each iteration, dendrograms are now created not only for V genes, but also for D and J genes. The file names are dendrogram_D.pdf, dendrogram_J.pdf

  • The V dendrograms are now in dendrogram_V.pdf (no longer V_dendrogram.pdf). This puts all the dendrograms together when looking at the files in the iteration directory.

  • The V_usage.tab and V_usage.pdf files are no longer created. Instead, expressed_V.tab and expressed_V.pdf are created. These contain similar information, but an allele-ratio filter is used to filter out artifacts.

  • Similarly, expressed_D.tab and expressed_J.tab and their .pdf counterparts are created in each iteration.

  • Removed parse subcommand (functionality is in the igblast subcommand)

  • New CDR3 detection method (only heavy chain sequences): CDR3 start/end coordinates are pre-computed using the database V and J sequences. Increases detection rate to 99% (previously less than 90%).

  • Remove the ability to check discovered genes for required motifs. This has never worked well.

  • Add a column clonotypes to the candidates.tab that tries to count how many clonotypes are associated with a single candidate (using only exact occurrences). This is intended to replace the CDR3s_exact column.

  • Add an exact_ratio to the germline filtering options. This checks the ratio between the exact V occurrence counts (exact column) between alleles.

  • Germline filtering option allele_ratio was renamed to clonotypes_ratio

  • Implement a cache for IgBLAST results. When the same dataset is re-analyzed, possibly with different parameters, the cached results are used instead of re-running IgBLAST, which saves a lot of time. If the V/D/J database or the IgBLAST version has changed, results are not re-used.

v0.8.0 (2017-06-20)

  • Add a barcodes_exact column to the candidates table. It gives the number of unique barcode sequences that were used by the sequences in the set of exact sequences. Also, add a configuration setting barcode_consensus that can turn off consensus taking of barcode groups, which needs to be set to false for barcodes_exact to work.

  • Add a Ds_exact column to candidates table.

  • Add a D_coverage configuration option.

  • The pre-processing filtering step no longer reads in the full table of IgBLAST assignments, but filters the table piece by piece. Memory usage for this step therefore does not depend anymore on the dataset size and should always be below 1 GB.

  • The functionality of the parse subcommand has been integrated into the igblast subcommand. This means that igdiscover igblast now directly outputs a result table (assigned.tab). This makes it easier to use that subcommand directly instead of only via the workflow.

  • The igblast subcommand now always runs makeblastdb by itself and deletes the BLAST database afterwards. This reduces clutter and ensures the database is always up to date.

  • Remove the library_name configuration setting. Instead, the library_name is now always the same as the name of analysis directory.

v0.7.0 (2017-05-04)

  • Add an “allele ratio” criterion to the germline filter to further reduce the number of false positives. The filter is activated by default and can be configured through the allele_ratio setting in the configuration file. See the documentation for how it works.

  • Ignore the CDR3-encoding bases whenever comparing two V gene sequences.

  • Avoid finding 5’-truncated V genes by extending found hits towards the 5’ end.

  • By default, candidate sequences are no longer merged if they are nearly identical. That is, the differences setting within the two germline filter configuration sections is now set to zero by default. Previously, we believed the merging would remove some false positives, but it turns out we also miss true positives. It also seems that with the other changes in this version we also no longer get the particular false positives the setting was supposed to catch.

  • Implement an experimental discoverj script for J gene discovery. It is curently not run automatically as part of igdiscover run. See igdiscover discoverj --help for how to run it manually.

  • Add a config subcommand, which can be used to change the configuration file from the command-line.

  • Add a V_CDR3_start column to the assigned.tab/filtered.tab tables. It describes where the CDR3 starts within the V sequence.

  • Similarly, add a CDR3_start column to the new_V_germline.tab file describing where the CDR3 starts within a discovered V sequence. It is computed by using the most common CDR3 start of the sequences within the cluster.

  • Rename the compose subcommand to germlinefilter.

  • The init subcommand automatically fixes certain problems in the input database (duplicate sequences, empty records, duplicate sequence names). Previously, it would complain, but the user would have to fix the problems themselves.

  • Move source code to GitHub

  • Set up automatic code testing (continuous integration) via Travis

  • Many documentation improvements

v0.6.0 (2016-12-07)

  • The FASTA files of the input V/D/J gene lists now need to be named V.fasta, D.fasta and J.fasta. The species name is no longer part of the file name. This should reduce confusion when working with species not supported by IgBLAST.

  • The species: configuration setting in the configuration can (and should) now be left empty. Its only use was that it is passed to IgBLAST, but since IgDiscover provides IgBLAST with its own V/D/J sequences anyway, it does not seem to make a difference.

  • A “cross-mapping” detection has been added, which should reduce the number of false positives. See the documentation for an explanation.

  • Novel sequences identical to a database sequence no longer get the _S1234 suffix.

  • No longer trim trim the initial G run in sequences (due to RACE) by default. It is now a configuration setting.

  • Add cdr3_location configuration setting: It allows to set whether to use a CDR3 in addition to the barcode for grouping sequences.

  • Create a groups.tab.gz file by default (describing the de-barcoded groups)

  • The pre-processing filter is now configurable. See the preprocessing_filter section in the configuration file.

  • Many improvements to the documentation

  • Extended and fixed unit tests. These are now run via a CI system.

  • Statistics in JSON format are written to stats/stats.json.

  • IgBLAST 1.5.0 output can now be parsed. Parsing is also faster by 25%.

  • More helpful warning message when no sequences were discovered in an iteration.

  • Drop support for Python 3.3.

v0.5 (2016-09-01)

  • V sequences of the input database are now whitelisted by default. The meaning of the whitelist configuration option has changed: If set to false, those sequences are no longer whitelisted. To whitelist additional sequences, create a whitelist.fasta file as before.

  • Sequences with stop codons are now filtered out by default.

  • Use more stringent germline filtering parameters by default.

v0.4 (2016-08-24)

  • It is now possible to install and run IgDiscover on OS X. Appropriate Conda packages are available on bioconda.

  • Add column has_stop to candidates.tab, which indicates whether the candidate sequence contains a stop codon.

  • Add a configuration option that makes it possible to disable the 5’ motif check by setting check_motifs: false (the looks_like_V column is ignored in this case).

  • Make it possible to whitelist known sequences: If a found gene candidate appears in that list, the sequence is included in the list of discovered sequences even when it would otherwise not pass filtering criteria. To enable this, just add a whitelist.fasta file to the project directory before starting the analysis.

  • The criteria for germline filter and pre-germline filter are now configurable: See germline_filter and pre_germline_filter sections in the configuration file.

  • Different runs of IgDiscover with the same parameters on the same input files will now give the same results. See the seed parameter in the configuration, also on how to get non-reproducible results as before.

  • Both the germline and pre-germline filter are now applied in each iteration. Instead of the new_V_database.fasta file, two files named new_V_germline.fasta and new_V_pregermline.fasta are created.

  • The compose subcommand now outputs a filtered version of the candidates.tab file in addition to a FASTA file. The table contains columns closest_whitelist, which is the name of the closest whitelist sequence, and whitelist_diff, which is the number of differences to that whitelist sequence.

v0.3 (2016-08-08)

  • Optionally, sequences are not renamed in the assigned.tab file, but retain their original name as in the FASTA or FASTQ file. Set rename: false in the configuration file to get this behavior.

  • Started an “advanced” section in the manual.

v0.2

  • IgDiscover can now also detect kappa and lambda light chain V genes (VK, VL)