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recount 1.31.2

SIGNIFICANT USER-VISIBLE CHANGES

  • Remove warnings related to using coverage_matrix() or expressed_regions() on Windows as rtracklayer::import() does work with local BigWig files on that operating system. I'm not sure if it will work with remote BigWig files given that remote BigWig file access on other operating systems is not working due to lawremi/rtracklayer#83 and related issues.

recount 1.29.1

BUG FIXES

  • Merged a pull request by @hpages which addresses some changes to GenomicFeatures. See #24 for details.

recount 1.19.2

BUG FIXES

recount 1.13.2

SIGNIFICANT USER-VISIBLE CHANGES

  • Documentation website is now available at https://leekgroup.github.io/recount/. It gets updated with every commit on the master branch (bioc-devel) using GitHub Actions and pkgdown.

recount 1.13.1

recount 1.11.14

  • Added a NEWS.md file to track changes to the package.

recount 1.11.13

NEW FEATURES

recount 1.11.12

BUG FIXES

recount 1.11.7

SIGNIFICANT USER-VISIBLE CHANGES

  • Renamed .load_install() as .load_check() as this function now only checks that the package(s) was installed and returns an error if missing. The error shows the user how to install the package(s) they are missing instead of installing them automatically. This complies with Marcel Ramos' request at #14.

recount 1.11.4

NEW FEATURES

  • Added the function download_retry() based on https://bioconductor.org/developers/how-to/web-query/ such that download_file() and other recount functions will re-try to download a file 3 times before giving up. This should help reduce the number of occasional failed Bioconductor nightly checks.

recount 1.9.7

SIGNIFICANT USER-VISIBLE CHANGES

  • Cleaned up the documentation of add_metadata() and changed the default source from recount_brain_v1 to recount_brain_v2.

recount 1.9.6

NEW FEATURES

  • citation('recount')[5] now lists the recount-brain bioRxiv pre-print citation information.

recount 1.9.5

NEW FEATURES

  • We have now released the FANTOM-CAT/recount2 RSE files which you can access now through download_study(type = 'rse-fc'). See Imada EL, Sanchez DF, et al, bioRxiv, 2019 https://www.biorxiv.org/content/10.1101/659490v1 for more information.

recount 1.9.4

BUG FIXES

  • I made the example code for geo_characteristics() more robust since currently rentrez can occasionally fails.

recount 1.9.3

NEW FEATURES

recount 1.9.2

BUG FIXES

recount 1.7.7

BUG FIXES

  • Updated reproduce_ranges() to match the URL change in Gencode from ftp:https://ftp.sanger.ac.uk to ftp:https://ftp.ebi.ac.uk

recount 1.7.5

SIGNIFICANT USER-VISIBLE CHANGES

  • add_metadata() can now download the recount_brain_v2 data.

recount 1.7.4

BUG FIXES

  • Fix a NOTE about RefManageR.

recount 1.7.3

SIGNIFICANT USER-VISIBLE CHANGES

  • Use BiocManager

recount 1.7.2

BUG FIXES

  • Fix a unit test.

recount 1.7.1

SIGNIFICANT USER-VISIBLE CHANGES

  • rse_tx URLs now point to v2 to reflect recent changes by Fu et al.

recount 1.5.11

BUG FIXES

  • Change some examples to dontrun and improve the code that cleans up after the tests. This should reduce the size of files left in tmp although they didn't seem too big to begin with.

recount 1.5.9

SIGNIFICANT USER-VISIBLE CHANGES

  • The functions add_metadata() and add_predictions() now return the sample metadata or predictions when the rse argument is missing.

recount 1.5.6

NEW FEATURES

  • Added the function add_metadata() which can be used to append curated metadata to a recount rse object. Currently, add_metadata() only supports the recount_brain_v1 data available at https://lieberinstitute.github.io/recount-brain/ and to be further described in Razmara et al, in prep, 2018.

recount 1.5.5

BUG FIXES

  • Fix doc link in geo_characteristics() which affected the Windows build machines.

recount 1.5.4

BUG FIXES

  • Fix a unit test for download_study(), add another test for the versions, and fix a NOTE in R CMD check.

recount 1.5.3

NEW FEATURES

  • download_study() can now download the transcript counts (rse_tx.RData) files. The transcript estimation is described in Fu et al, 2018.

SIGNIFICANT USER-VISIBLE CHANGES

  • download_study() now has a version parameter (defaults to 2). This argument controls which version of the files to download based on the change on how exons were defined. Version 1 are reduced exons while version 2 are disjoint exons as described in further detail in the documentation tab of the recount website https://jhubiostatistics.shinyapps.io/recount/.
  • recount_url and the example rse_gene_SRP009615 have been updated to match the changes in version 2.

recount 1.3.13

BUG FIXES

  • Changed reproduce_ranges() since disjoint exons are more useful than reduced exons for downstream analyses.

recount 1.3.12

NEW FEATURES

  • Added the function read_counts().

recount 1.3.9

SIGNIFICANT USER-VISIBLE CHANGES

recount 1.3.7

SIGNIFICANT USER-VISIBLE CHANGES

  • add_predictions() was bumped to version 0.0.05

recount 1.3.5

SIGNIFICANT USER-VISIBLE CHANGES

  • Vignette now uses the new BiocStyle::html_document that was recently released.

recount 1.3.2

NEW FEATURES

  • coverage_matrix() now has two new arguments: scale and round. Use scale = FALSE to get raw coverage counts, which you can then scale with scale_counts(). scale is set to TRUE by default, so the counts are scaled to a library size of 40 million reads. round is set to FALSE by default, but can be set to TRUE if you want to get integer counts, just as in the default of scale_counts().

recount 1.3.1

SIGNIFICANT USER-VISIBLE CHANGES

  • Changed the default version argument of add_predictions() to latest. Internally, that's still 0.0.03.

recount 1.1.27

NEW FEATURES

  • Added the add_predictions() function which appends the predicted phenotypes to a RSE object downloaded with recount. The phenotypes were predicted by Shannon Ellis et al, 2017 (citation coming up soon!).

recount 1.1.26

SIGNIFICANT USER-VISIBLE CHANGES

recount 1.1.25

NEW FEATURES

  • Added the function getRPKM() which can be used with RangedSummarizedExperiment objects from recount and from other sources.

recount 1.1.24

SIGNIFICANT USER-VISIBLE CHANGES

  • recount_url now includes the URLs for the GTEx bigWig files.

recount 1.1.19

SIGNIFICANT USER-VISIBLE CHANGES

  • coverage_matrix() now returns a RangedSummarizedExperiment object. This matches the behavior of recount.bwtool::coverage_matrix_bwtool() and is more consistent with the use of RSE objects in recount.

recount 1.1.18

BUG FIXES

  • coverage_matrix()'s helper function .read_pheno() was failing for some projects.

recount 1.1.16

BUG FIXES

  • Fixed a bug in the counts in coverage_matrix(). They were being incorrectly multiplied by 100.

recount 1.1.14

SIGNIFICANT USER-VISIBLE CHANGES

  • Completed the change to Gencode v25 annotation for exon and gene counts.

recount 1.1.13

SIGNIFICANT USER-VISIBLE CHANGES

  • We dropped TxDb.Hsapiens.UCSC.hg38.knownGene completely from recount and will be using Gencode v25 instead.

recount 1.1.12

BUG FIXES

  • Updated snaptron_query() to comply with recent changes in Snaptron.

recount 1.1.8

SIGNIFICANT USER-VISIBLE CHANGES

  • Updated the package so you can now access TCGA data. Now there's over 8 terabytes of data available in the recount project!

recount 1.1.6

SIGNIFICANT USER-VISIBLE CHANGES

  • snaptron_query() can now access GTEx and TCGA data.

recount 1.1.5

SIGNIFICANT USER-VISIBLE CHANGES

  • Snaptron changed from stingray.cs.jhu.edu:8090 to snaptron.cs.jhu.edu so snaptron_query() has been changed accordingly.

recount 1.1.2

SIGNIFICANT USER-VISIBLE CHANGES

  • The function reproduce_ranges() now has the db argument. By default it's set to TxDb.Hsapiens.UCSC.hg38.knownGene to reproduce the actual information used in recount. But it can also be used with EnsDb.Hsapiens.v79 to use the ENSEMBL annotation. Then with coverage_matrix() you can get the counts for either an updated TxDb.Hsapiens.UCSC.hg38.knownGene or for EnsDb.Hsapiens.v79 at the exon and/or gene levels as shown in the vignette.

recount 1.1.1

SIGNIFICANT USER-VISIBLE CHANGES

  • The vignette now describes how to download all the data, how to check exon-exon junctions by class, and how to use SciServer compute to access all the recount data (over 6 TB) via https://www.sciserver.org/

recount 0.99.30

NEW FEATURES

  • Added the function snaptron_query() which queries Intropolis via Snaptron to find if an exon-exon junction is present in the data.

recount 0.99.29

BUF FIXES

  • Fixed an bug in the vignette. Thanks to Michael Love for noticing it!

recount 0.99.0

NEW FEATURES

  • Created the package skeleton for recount
  • Added the function reproduce_ranges() for re-creating the gene or exon level information used in the recount project.
  • Added the function abstract_search() for identifying SRA projects of interest by searching the abstracts.
  • Added the function browse_study() for opening a browser tab for further exploring a project.
  • Added the function download_study() for downloading the data from the recount project.
  • Added the function scale_counts() for properly scaling the counts before performing a differential expression analysis with the RangedSummarizedExperiment objects hosted in the recount project.
  • Added the function expressed_regions() for defining the expressed regions in a chromosome for a given SRA study.
  • Added the function coverage_matrix() for computing the coverage matrix based on the regions of interest for a given SRA study.
  • Added the function geo_info() for obtaining sample information from GEO.
  • Added the function find_geo() for finding the GEO accession id given a SRA run accession (id). This function will be useful for SRA projects that did not have GEO entries at the time recount's data was created.
  • Added the function geo_characteristics() for building a data.frame() from geo_info()'s results for the characteristics.
  • Added the function all_metadata() which downloads all the phenotype data for all projects. This function can be useful for identifying projects and/or samples of interests.