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Merge pull request #699 from maxplanck-ie/dev_ksikora2
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DESeq2 minor fixes
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katsikora committed Oct 7, 2020
2 parents 1288303 + 7c7cc2a commit 515b44c
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Showing 12 changed files with 18 additions and 20 deletions.
2 changes: 1 addition & 1 deletion conda-recipe/meta.yaml
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@@ -1,6 +1,6 @@
package:
name: snakepipes
version: 2.2.3
version: 2.3.0

source:
path: ../
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4 changes: 3 additions & 1 deletion docs/content/News.rst
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@@ -1,11 +1,13 @@
snakePipes News
===============

snakePipes 2.x.y
snakePipes 2.3.0
----------------

* Deprecated mode Gruen in scRNAseq.
* scRNAseq mode Alevin now outputs spliced/unspliced counts for RNA velocity estimation based on Soneson et al. 2020, bioRxiv https://doi.org/10.1101/2020.03.13.990069 .
* Fixed "external_gene_name" and "Status" columns in DESeq2 html report.
* Removed warning when sample names start with a number.


snakePipes 2.2.3
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2 changes: 1 addition & 1 deletion docs/content/setting_up.rst
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Expand Up @@ -34,7 +34,7 @@ The easiest way to install snakePipes is via our conda channel. The following co

.. code:: bash
conda create -n snakePipes -c mpi-ie -c conda-forge -c bioconda snakePipes==2.2.3
conda create -n snakePipes -c mpi-ie -c conda-forge -c bioconda snakePipes==2.3.0
This way, the software used within snakePipes do not conflict with the software pre-installed on your terminal or in your python environment.

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4 changes: 3 additions & 1 deletion docs/content/workflows/scRNA-seq.rst
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Expand Up @@ -6,7 +6,7 @@ scRNA-seq
What it does
------------

The scRNA-seq pipeline is intended to process UMI-based data, expecting the cell barcode and umi in Read1, and the cDNA sequence in Read2.
The scRNA-seq pipeline is intended to process UMI-based data, expecting the cell barcode and umi in Read1, and the cDNA sequence in Read2. The workflow has predefined settings for CelSeq2 and 10x data, but can be extended to custom protocols.

There are currently two analysis modes available:
- "STARsolo" which uses STAR solo for mapping and quantitation.
Expand Down Expand Up @@ -145,6 +145,8 @@ Fraction of read length required to overlap the intron
~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~

In mode Alevin, the fraction of read length required to overlap the intron in order to be counted as "unspliced" is set to 0.2 (i.e. 20%) by default. This corresponds to 10nt in a 50nt-long read, or to 20nt in a 100nt-long read. The user is encouraged to modify this value as deemed appropriate via the ``--readLengthFrx`` commandline argument.
In practice, this variable affects the length of the exon sequence flank added to the intron sequence to generate reference sequences for Salmon Alevin. Exon sequence flank length is set to one minus 'readLengthFrx' of read length.



Output structure
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2 changes: 1 addition & 1 deletion docs/index.rst
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Expand Up @@ -34,7 +34,7 @@ Quick start

.. code:: bash
conda create -n snakePipes -c mpi-ie -c conda-forge -c bioconda snakePipes==2.1.1
conda create -n snakePipes -c mpi-ie -c conda-forge -c bioconda snakePipes==2.3.0
* You can update snakePipes to the latest version available on conda with:

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2 changes: 1 addition & 1 deletion snakePipes/__init__.py
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@@ -1 +1 @@
__version__ = '2.2.3'
__version__ = '2.3.0'
4 changes: 2 additions & 2 deletions snakePipes/shared/rscripts/DESeq2Report.Rmd
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Expand Up @@ -430,10 +430,10 @@ if(!is.null(searchURL) & outputIsHTML) {
for(i in which(colnames(res.df) %in% c('pvalue', 'padj'))) res.df[, i] <- format(res.df[, i], scientific = TRUE)
if(outputIsHTML) {
datatable(head(res.df, n = nBest), options = list(pagingType='full_numbers', pageLength=10, scrollX='100%'), escape = FALSE, rownames = FALSE) %>% formatRound(which(!colnames(res.df) %in% c('pvalue', 'padj', 'Feature')), digits)
datatable(head(res.df, n = nBest), options = list(pagingType='full_numbers', pageLength=10, scrollX='100%'), escape = FALSE, rownames = FALSE) %>% formatRound(which(!colnames(res.df) %in% c('pvalue', 'padj', 'Feature','Status','external_gene_name')), digits)
} else {
res.df_top <- head(res.df, n = 20)
for(i in which(!colnames(res.df) %in% c('pvalue', 'padj', 'Feature'))) res.df_top[, i] <- round(res.df_top[, i], digits)
for(i in which(!colnames(res.df) %in% c('pvalue', 'padj', 'Feature','Status','external_gene_name'))) res.df_top[, i] <- round(res.df_top[, i], digits)
kable(res.df_top)
}
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10 changes: 5 additions & 5 deletions snakePipes/shared/rscripts/noncoding-DESeq2.R
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Expand Up @@ -77,12 +77,12 @@ bib <- c(
DESeq2 = citation('DESeq2'))

write.bibtex(bib, file = 'citations.bib')
file.copy(paste0(snakemake@scriptdir, "/DESeq2Report.Rmd"), to = 'DESeq2_report_basic.Rmd')
file.copy(paste0(snakemake@scriptdir, "/DESeq2Report.Rmd"), to = file.path(snakemake@params["outdir"],'DESeq2_report_basic.Rmd'))

## TODO we need 4 of these...
outprefix = "DEseq_basic"
cite_options(citation_format="text", style="html", cite.style="numeric", hyperlink=TRUE)
render('DESeq2_report_basic.Rmd',
render(file.path(snakemake@params["outdir"],'DESeq2_report_basic.Rmd'),
output_file = paste0(snakemake@params["outdir"], "/DESeq2_report_genes.html"),
output_format = "html_document",
clean = TRUE,
Expand All @@ -95,7 +95,7 @@ render('DESeq2_report_basic.Rmd',
heatmap_topN = 20,
geneNamesFile = geneNamesFilePath))

render('DESeq2_report_basic.Rmd',
render(file.path(snakemake@params["outdir"],'DESeq2_report_basic.Rmd'),
output_file = paste0(snakemake@params["outdir"], "/DESeq2_report_repeat_name.html"),
output_format = "html_document",
clean = TRUE,
Expand All @@ -108,7 +108,7 @@ render('DESeq2_report_basic.Rmd',
heatmap_topN = 20,
geneNamesFile = geneNamesFilePath))

render('DESeq2_report_basic.Rmd',
render(file.path(snakemake@params["outdir"],'DESeq2_report_basic.Rmd'),
output_file = paste0(snakemake@params["outdir"], "/DESeq2_report_repeat_class.html"),
output_format = "html_document",
clean = TRUE,
Expand All @@ -121,7 +121,7 @@ render('DESeq2_report_basic.Rmd',
heatmap_topN = 20,
geneNamesFile = geneNamesFilePath))

render('DESeq2_report_basic.Rmd',
render(file.path(snakemake@params["outdir"],'DESeq2_report_basic.Rmd'),
output_file = paste0(snakemake@params["outdir"], "/DESeq2_report_repeat_family.html"),
output_format = "html_document",
clean = TRUE,
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2 changes: 1 addition & 1 deletion snakePipes/shared/rules/tecounts.snakefile
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Expand Up @@ -196,7 +196,7 @@ if sampleSheet:
benchmark:
"{}/.benchmark/DESeq2.featureCounts.benchmark".format(get_outdir("DESeq2",sampleSheet))
params:
outdir = get_outdir("DESeq2", sampleSheet),
outdir = os.path.join(outdir, get_outdir("DESeq2", sampleSheet)),
fdr = 0.05,
conda: CONDA_RNASEQ_ENV
script: "../rscripts/noncoding-DESeq2.R"
2 changes: 0 additions & 2 deletions snakePipes/workflows/mRNA-seq/Snakefile
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Expand Up @@ -21,8 +21,6 @@ include: os.path.join(workflow.basedir, "internals.snakefile")
### include modules of other snakefiles ########################################
################################################################################

cf.namesOKinR(samples)

# deeptools cmds
include: os.path.join(maindir, "shared", "tools" , "deeptools_cmds.snakefile")

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2 changes: 0 additions & 2 deletions snakePipes/workflows/noncoding-RNA-seq/Snakefile
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Expand Up @@ -53,8 +53,6 @@ include: os.path.join(maindir, "shared", "rules", "tecounts.snakefile")
## MultiQC
include: os.path.join(maindir, "shared", "rules", "multiQC.snakefile")

cf.namesOKinR(samples)

### conditional/optional rules #################################################
################################################################################
def run_FastQC(fastqc):
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2 changes: 0 additions & 2 deletions snakePipes/workflows/scRNAseq/Snakefile
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Expand Up @@ -51,8 +51,6 @@ include: os.path.join(maindir, "shared", "tools" , "deeptools_cmds.snakefile")
include: os.path.join(maindir, "shared", "rules", "deepTools_RNA.snakefile")
include: os.path.join(maindir, "shared", "rules", "multiQC.snakefile")

cf.namesOKinR(samples)


### conditional/optional rules #################################################
################################################################################
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