From d1c7881c902ea8dcbd31001ba710e30f8cda1516 Mon Sep 17 00:00:00 2001 From: Hirak Sarkar Date: Tue, 5 Feb 2019 18:09:31 -0500 Subject: [PATCH 1/3] Update README.md --- README.md | 9 +++++++-- 1 file changed, 7 insertions(+), 2 deletions(-) diff --git a/README.md b/README.md index a294f64..528bc05 100644 --- a/README.md +++ b/README.md @@ -1,6 +1,5 @@ -[docker](docker pull hrksrkr/minnow) -[tutorial](https://combine-lab.github.io/alevin-tutorial/2019/running-minnow/) + [![Build Status](https://travis-ci.org/COMBINE-lab/salmon.svg?branch=master)](https://travis-ci.org/COMBINE-lab/salmon) # Minnow ( read level simulator for dscRNA-seq data) @@ -13,6 +12,12 @@ Minnow is a read level simulator for droplet based single cell RNA-seq data. Min

+## Pre-build images + +[docker](`docker pull hrksrkr/minnow`) + +[tutorial](https://combine-lab.github.io/alevin-tutorial/2019/running-minnow/) + ## Installation Minnow is written in C++14 and tested in a ubuntu server, please let us know if you have difficulty compiling it in your own machine. From 3cb1b884621ba8c92d788781a442f253da7b2fbd Mon Sep 17 00:00:00 2001 From: Hirak Sarkar Date: Tue, 5 Feb 2019 18:09:59 -0500 Subject: [PATCH 2/3] Update README.md --- README.md | 3 --- 1 file changed, 3 deletions(-) diff --git a/README.md b/README.md index 528bc05..9c74093 100644 --- a/README.md +++ b/README.md @@ -1,7 +1,4 @@ - - [![Build Status](https://travis-ci.org/COMBINE-lab/salmon.svg?branch=master)](https://travis-ci.org/COMBINE-lab/salmon) - # Minnow ( read level simulator for dscRNA-seq data) Most analysis pipelines validate their results using known marker genes (which are not widely available for all types of analysis) and by using simulated data from gene-count-level simulators. Typically, the impact of using different read-alignment or UMI deduplication methods has not been widely explored. Assessments based on simulation tend to start at the level of assuming a simulated count matrix, ignoring the effect that different approaches for resolving UMI counts from the raw read data may produce. Here, we present minnow, a comprehensive sequence-level droplet-based single-cell RNA-seq (dscRNA-seq) experiment simulation framework. Minnow accounts for important sequence-level characteristics of experimental scRNA-seq datasets and models effects such as PCR amplification, CB (cellular barcodes) and UMI (Unique Molecule Identifiers) selection, and sequence fragmentation and sequencing. From 6a613501b22e85e10ba8d101fae8121eb6676117 Mon Sep 17 00:00:00 2001 From: Hirak Sarkar Date: Tue, 5 Feb 2019 18:11:50 -0500 Subject: [PATCH 3/3] Update README.md --- README.md | 2 +- 1 file changed, 1 insertion(+), 1 deletion(-) diff --git a/README.md b/README.md index 9c74093..3d859ff 100644 --- a/README.md +++ b/README.md @@ -1,4 +1,4 @@ -[![Build Status](https://travis-ci.org/COMBINE-lab/salmon.svg?branch=master)](https://travis-ci.org/COMBINE-lab/salmon) +[![Build Status](https://travis-ci.org/COMBINE-lab/minnow.svg?branch=master)](https://travis-ci.org/COMBINE-lab/minnow) # Minnow ( read level simulator for dscRNA-seq data) Most analysis pipelines validate their results using known marker genes (which are not widely available for all types of analysis) and by using simulated data from gene-count-level simulators. Typically, the impact of using different read-alignment or UMI deduplication methods has not been widely explored. Assessments based on simulation tend to start at the level of assuming a simulated count matrix, ignoring the effect that different approaches for resolving UMI counts from the raw read data may produce. Here, we present minnow, a comprehensive sequence-level droplet-based single-cell RNA-seq (dscRNA-seq) experiment simulation framework. Minnow accounts for important sequence-level characteristics of experimental scRNA-seq datasets and models effects such as PCR amplification, CB (cellular barcodes) and UMI (Unique Molecule Identifiers) selection, and sequence fragmentation and sequencing.