---
title: "External data"
output: html_document
---

```{r setup, include=FALSE}
knitr::opts_chunk$set(echo = TRUE)
```

# DF_cell_types.txt file
`DF_cell_types.txt` contains a \code{data.frame} with the matching between cell id (1st column) and cell-types (2nd column) from the data stored in the `alevin-fry` folder.
The cell-types were obtained from the original study of [Velasco et al. (2019)](https://www.nature.com/articles/s41586-019-1289-x), and are publicly available via [meta_combined.txt](https://singlecell.broadinstitute.org/single_cell/study/SCP282/reproducible-brain-organoids#study-download) file.

Below is the script used to create the `DF_cell_types.txt` object.
```r
# load internal data to the package:
data_dir = system.file("extdata", package = "DifferentialRegulation")
# specify samples ids:
sample_ids = paste0("organoid", c(1:3, 16:18))
# set directories of each sample input data (obtained via alevin-fry):
base_dir = file.path(data_dir, "alevin-fry", sample_ids)
file.exists(base_dir)
# load USA sce:
path_to_counts = file.path(base_dir,"/alevin/quants_mat.mtx")
path_to_cell_id = file.path(base_dir,"/alevin/quants_mat_rows.txt")
path_to_gene_id = file.path(base_dir,"/alevin/quants_mat_cols.txt")

file.exists(path_to_counts)
file.exists(path_to_cell_id)
file.exists(path_to_gene_id)

library(DifferentialRegulation)
sce = load_USA(path_to_counts,
               path_to_cell_id,
               path_to_gene_id,
               sample_ids)

# load pre-computed cell-types, from the original study
md <- read.csv("../REAL data/discovery - brain human organoids/data/meta_combined.txt", sep = "\t")
md <- md[grepl("PGP1", md$Batch), ]
md$SEQ <- sapply(md$NAME, FUN = function (x) strsplit(x, split = "_")[[1]][3])

# keep organoids 1:3 and 16:18 only
md = md[ md$Organoid %in% c("1", "2", "3", "16", "17", "18"), ]
table(md$Organoid)
md$Organoid = as.numeric(md$Organoid)

md$cell_id = paste0("organoid", md$Organoid, ".", md$SEQ)
matches = match(colnames(sce), md$cell_id)

DF_cell_types = data.frame(cell_id  = md$cell_id[matches],
                           cell_type = md$CellType[matches],
                           row.names = NULL)
table(DF_cell_types$cell_type)

write.csv(DF_cell_types, file = "DF_cell_types.csv")

write.table(DF_cell_types, file = "DF_cell_types.txt", sep = "\t",
            row.names = FALSE, col.names = TRUE)

# check loaded object is identical:
DF_cell_types_reload = read.csv("DF_cell_types.txt", sep = "\t", header = TRUE)
```

# alevin-fry folder

## Data
We use a real droplet scRNA-seq dataset from Velasco et al. (2019), Nature 570 (7762): 523–27.
In particular, we compare two groups of three samples, consisting of human brain organoids, cultured for 3 and 6 months.
For computational reasons, we stored a subset of this dataset, in our package, consisting of 100 genes and 3,493 cells, belonging to two cell-types.
Cell-type assignment was done in the original styudy (Velasco et al., 2019), and is publicly available in the `meta_combined.txt` file [here](https://singlecell.broadinstitute.org/single_cell/study/SCP282/reproducible-brain-organoids#study-download).

Raw data can also be downloaded [here](https://www.ncbi.nlm.nih.gov/Traces/study/?acc=PRJNA531650&o=acc_s%3Aa).

## Download data
Download the raw data.
``` bash
wget https://sra-pub-src-1.s3.amazonaws.com/SRR8869247/Org1_possorted_genome_bam.bam.1 -O SRR8869247.bam && \ 
bamtofastq SRR8869247.bam SRR8869247 --nthreads=32 && rm -rf SRR8869247.bam
wget https://sra-pub-src-1.s3.amazonaws.com/SRR8869248/Org2_possorted_genome_bam.bam.1 -O SRR8869248.bam && \
bamtofastq SRR8869248.bam SRR8869248 --nthreads=32 && rm -rf SRR8869248.bam
wget https://sra-pub-src-1.s3.amazonaws.com/SRR8869249/Org3_possorted_genome_bam.bam.1 -O SRR8869249.bam && \
bamtofastq SRR8869249.bam SRR8869249 --nthreads=32 && rm -rf SRR8869249.bam
wget https://sra-pub-src-1.s3.amazonaws.com/SRR8869262/Org16_possorted_genome_bam.bam.1 -O SRR8869262.bam && \
bamtofastq SRR8869262.bam SRR8869262 --nthreads=32 && rm -rf SRR8869262.bam
wget https://sra-pub-src-1.s3.amazonaws.com/SRR8869263/Org17_possorted_genome_bam.bam.1 -O SRR8869263.bam && \
bamtofastq SRR8869263.bam SRR8869263 --nthreads=32 && rm -rf SRR8869263.bam
wget https://sra-pub-src-1.s3.amazonaws.com/SRR8869264/Org18_possorted_genome_bam.bam.1 -O SRR8869264.bam && \
bamtofastq SRR8869264.bam SRR8869264 --nthreads=32 && rm -rf SRR8869264.bam
```

## Genome
Download the reference genome.
``` r
path <- "brain_human/01_annotation/"
fa_file <- "GRCh38.primary_assembly.genome.fa"
gtf_file <- "gencode.v37.primary_assembly.annotation.gtf.gz"

# download data
if (!file.exists(paste0(path, fa_file))) {
download.file(url = "ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_37/GRCh38.primary_assembly.genome.fa.gz",
destfile = paste0(path, fa_file, ".gz"))
gunzip(paste0(path, fa_file, ".gz"))
}

if (!file.exists(paste0(path, gtf_file))) {
download.file(url = "ftp://ftp.ebi.ac.uk/pub/databases/gencode/Gencode_human/release_37/gencode.v37.primary_assembly.annotation.gtf.gz",
destfile = paste0(path, gtf_file))
}
```

## Alignment via *alevin-fry*
Run `make_splici_txome` function, from [roe](https://github.com/COMBINE-lab/roe) R package.
``` r
# splici txome for human data
gtf_path <- file.path("brain_human/01_annotation/gencode.v37.annotation.gtf.gz")
genome_path = file.path("brain_human/01_annotation/GRCh38.primary_assembly.genome.fa")
read_length = 91
flank_trim_length = 5
output_dir = file.path("brain_human/01_annotation/splici/")

library(roe)

make_splici_txome(gtf_path = gtf_path, 
genome_path = genome_path, 
read_length = read_length, 
flank_trim_length = flank_trim_length, 
output_dir = output_dir)
```

Run *alevin*.
``` bash
salmon index \
-t brain_human/01_annotation/splici/transcriptome_splici.fa \
-i brain_human/01_annotation/splici/index_folder \
--gencode -p 32

## ORGANOID 1
salmon alevin -l ISR -i brain_human/01_annotation/splici/index_folder \
-1 brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
-2 brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L002_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L002_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L002_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L002_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869247/s1_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
-o brain_human/02_alevin_for_fry/organoid1/ -p 32 --chromium --sketch

## ORGANOID 2
salmon alevin -l ISR -i brain_human/01_annotation/splici/index_folder \
-1 brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
-2 brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L002_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L002_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L002_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L002_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869248/s2_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
-o brain_human/02_alevin_for_fry/organoid2/ -p 32 --chromium --sketch

## ORGANOID 3
salmon alevin -l ISR -i brain_human/01_annotation/splici/index_folder \
-1 brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
-2 brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L002_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_H7WTJBGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L002_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HFM7TBGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L002_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HHT33BGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L002_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869249/s3_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
-o brain_human/02_alevin_for_fry/organoid3/ -p 32 --chromium --sketch

## ORGANOID 16
salmon alevin -l ISR -i brain_human/01_annotation/splici/index_folder \
-1 brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L002_R1_002.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L003_R1_002.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L001_R1_002.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L002_R1_002.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L003_R1_002.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L004_R1_002.fastq.gz \
-2 brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L002_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L002_R2_002.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L003_R2_002.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L001_R2_002.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L001_R2_002.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L003_R2_002.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869262/s4_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L004_R2_002.fastq.gz \
-o brain_human/02_alevin_for_fry/organoid16/ -p 32 --chromium --sketch

## ORGANOID 17
salmon alevin -l ISR -i brain_human/01_annotation/splici/index_folder \
-1 brain_human/03_data/fastq/SRR8869263/s5_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869263/s5_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869263/s5_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869263/s5_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869263/s5_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869263/s5_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869263/s5_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869263/s5_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
-2 brain_human/03_data/fastq/SRR8869263/s5_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869263/s5_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L002_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869263/s5_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869263/s5_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869263/s5_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869263/s5_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L002_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869263/s5_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869263/s5_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
-o brain_human/02_alevin_for_fry/organoid17/ -p 32 --chromium --sketch

## ORGANOID 18
salmon alevin -l ISR -i brain_human/01_annotation/splici/index_folder \
-1 brain_human/03_data/fastq/SRR8869264/s6_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869264/s6_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869264/s6_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869264/s6_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869264/s6_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L001_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869264/s6_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L002_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869264/s6_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L003_R1_001.fastq.gz \
brain_human/03_data/fastq/SRR8869264/s6_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L004_R1_001.fastq.gz \
-2 brain_human/03_data/fastq/SRR8869264/s6_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869264/s6_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L002_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869264/s6_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869264/s6_MissingLibrary_1_HMWNVBGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869264/s6_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L001_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869264/s6_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L002_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869264/s6_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L003_R2_001.fastq.gz \
brain_human/03_data/fastq/SRR8869264/s6_MissingLibrary_1_HTW2HBGX5/bamtofastq_S1_L004_R2_001.fastq.gz \
-o brain_human/02_alevin_for_fry/organoid18/ -p 32 --chromium --sketch
```

Run *alevin-fry*.
``` bash
samples=(1 2 3 16 17 18)

for sample in ${samples[@]}
do
alevin-fry generate-permit-list \
-i brain_human/02_alevin_for_fry/organoid${sample} \
-o brain_human/05_alevin_fry/organoid${sample} \
-k -d fw

alevin-fry collate \
-r brain_human/02_alevin_for_fry/organoid${sample} \
-i brain_human/05_alevin_fry/organoid${sample} \
-t 32

alevin-fry quant \
-i brain_human/05_alevin_fry/organoid${sample} \
-o brain_human/05_alevin_fry/organoid${sample} \
-m brain_human/01_annotation/splici/transcriptome_splici_t2g_3col.tsv \
-t 32 --use-mtx -d -r cr-like-em
done
```

## Selection of 100 genes only
To make the example portable, we selected 100 genes and cells from 2 cell types only (RG and Cycling).
``` r
rm(list = ls())

# specify 4 samples ids:
sample_ids = paste0("organoid", c(1:3, 16:18))
# set directories of each sample input data (obtained via alevin-fry):
base_dir = file.path("human alevin-fry", sample_ids, "alevin")

path_to_counts = file.path(base_dir,"quants_mat.mtx")
path_to_cell_id = file.path(base_dir,"quants_mat_rows.txt")
path_to_gene_id = file.path(base_dir,"quants_mat_cols.txt")
path_to_EC_counts = file.path(base_dir,"geqc_counts.mtx")
path_to_EC = file.path(base_dir,"gene_eqclass.txt.gz")

n_genes_keep = 100
for(i in seq_along(sample_ids)){
############################################################################################################
# quants_mat_rows.txt: cell id
############################################################################################################
library(data.table)
cell_id = fread(path_to_cell_id[[i]],
sep = " ", quote = "", header = FALSE)

# assign cell types
md <- read.csv("meta_combined.txt", sep = "\t")
md <- md[grepl("PGP1", md$Batch), ]
md$SEQ <- sapply(md$NAME, FUN = function (x) strsplit(x, split = "_")[[1]][3])

# keep organoids 1:3 and 16:18 only
md = md[ md$Organoid %in% c("1", "2", "3", "16", "17", "18"), ]
table(md$Organoid)
# rename organoids 16:18 as 4:6
md$Organoid[md$Organoid == "16"]  = "4"
md$Organoid[md$Organoid == "17"]  = "5"
md$Organoid[md$Organoid == "18"]  = "6"

md$Organoid = as.numeric(md$Organoid)
table(md$Organoid)

md = md[md$Organoid == i, ]

matches = match(cell_id$V1, md$SEQ)
head(cell_id$V1); head(md$SEQ[matches])
tail(cell_id$V1); tail(md$SEQ[matches])

cell_type <- md$CellType[matches]
rm(md); rm(matches)

sel_cells = cell_type %in% c("RG", "Cycling")
sel_cells[is.na(sel_cells)] = FALSE
table(sel_cells)

cell_id = cell_id[sel_cells,]

colnames(cell_id) = NULL

file_name = file.path("alevin-fry", sample_ids[i], "alevin/quants_mat_rows.txt")
fwrite(cell_id, file = file_name)

cell_id_reload = fread(file_name, 
sep = " ", quote = "", header = FALSE)

# OK, same sizer and content:
dim(cell_id_reload); dim(cell_id)
print(all(cell_id_reload == cell_id))

############################################################################################################
# quants_mat.mtx: USA estimated counts
############################################################################################################
library(Matrix)
counts = readMM(path_to_counts[[i]])

# sel cells from above:
counts = counts[sel_cells,]

n_genes = ncol(counts)/3

# first n_genes refer to S
# second n_genes refer to U
# third n_genes refer to A
spliced  = counts[, seq.int(1, n_genes) ]
unspliced = counts[, seq.int(n_genes+1, 2*n_genes)]
ambiguous = counts[, seq.int(2*n_genes+1, 3*n_genes)]

counts_keep = cbind(spliced[, seq_len(n_genes_keep) ], 
unspliced[, seq_len(n_genes_keep)],
ambiguous[, seq_len(n_genes_keep)])

file_name = file.path("alevin-fry", sample_ids[i], "alevin/quants_mat.mtx")
writeMM(counts_keep, file = file_name)

counts_reload = readMM(file_name)
# OK, same sizer and content:
dim(counts_reload); dim(counts_keep)
print(all(counts_keep == counts_reload))

############################################################################################################
# quants_mat_cols.txt: gene id
############################################################################################################
gene_id = fread(path_to_gene_id[[i]],
sep = " ", quote = "", header = FALSE)
n_genes_original = nrow(gene_id)/3

sel = seq_len(n_genes_keep)
gene_id_keep = gene_id[c(sel,
n_genes_original + sel,
2 * n_genes_original+sel)]
colnames(gene_id_keep) = NULL

file_name = file.path("alevin-fry", sample_ids[i], "alevin/quants_mat_cols.txt")
fwrite(gene_id_keep, file = file_name)

gene_id_reload = fread(file_name, 
sep = " ", quote = "", header = FALSE)

# OK, same sizer and content:
dim(gene_id_reload); dim(gene_id_keep)
print(all(gene_id_reload == gene_id_keep))

############################################################################################################
# ECs ids:
############################################################################################################
# load ECs: 
EC_genes = fread(path_to_EC[[i]],
sep = " ", quote = "", header = FALSE)[[1]]

# remove first 2 numbers:
EC_genes = EC_genes[-c(1,2)]  
# 1st number: number of transcripts (n_genes * 3)
# 2nd number: number of equivalence classes

# load EC counts
EC_counts = readMM(path_to_EC_counts[[i]])

# select cells
EC_counts_keep = EC_counts[sel_cells, ]

# remove ECs with 0 counts:
sel_non_zero_ECs = colSums(EC_counts_keep) > 0
EC_genes = EC_genes[sel_non_zero_ECs]

n_EC  = length(EC_genes)
# load EC info:
X = EC_genes[seq_len(n_EC)] # vector with all transcript ids
# split info separated by "\t":
X = strsplit(X,"\t",fixed=TRUE)
# turn character ids into numeric:
X = lapply(X, as.integer)

# ECs id, corresponds to rows in EC 
EC_id = 1 + vapply(X, function(x){
x[length(x)]
}, FUN.VALUE = integer(1))

# ECs gene ids, as in "gene_id" file.
EC_gene_id = lapply(X, function(x){
x[-length(x)]
})
rm(X)

# keep initial n_genes_keep genes, then NA (genes to be removed):
seq_to_rep = c(seq_len(n_genes_keep)-1, rep(NA, n_genes - n_genes_keep))
transform_ids = c(seq_to_rep, 
seq_to_rep + n_genes_keep,
seq_to_rep + 2*n_genes_keep)

# transform gene ids -> keep initial n_genes_keep genes, then NA (genes to be removed):
EC_gene_id = lapply(EC_gene_id, function(x){
transform_ids[x + 1]
})

# remove NAs (genes removed)
EC_gene_id = lapply(EC_gene_id, function(x){
x[!is.na(x)]
})

# keep only ECs with at least 1 element:
keep_ECs = sapply(EC_gene_id, length) > 0.5
EC_gene_id = EC_gene_id[keep_ECs]
EC_id = EC_id[keep_ECs]

# store this ECs to be saved
keep_EC_matrix = EC_id

# set EC_id to 0, ..., n_ECs - 1
EC_id = seq_along(keep_EC_matrix)-1

n_EC_keep = length(EC_id)

# merge gene ids and EC ids:
XX = lapply(seq_len(n_EC_keep), function(i){
paste( c( unlist(EC_gene_id[[i]]), EC_id[[i]]), collapse =  "\t")
})

# create new EC object
XX = c(n_genes_keep * 3, # n_genes kept
n_EC_keep,
XX)    # n_ECs kept

XX = data.table(XX)
colnames(XX) = NULL

file_name = file.path("alevin-fry", sample_ids[i], "alevin/gene_eqclass.txt.gz")
fwrite(XX, file = file_name)

EC_genes_reload = fread(file_name,
sep = " ", quote = "", header = FALSE)

# OK, same sizer and content:
dim(EC_genes_reload); dim(XX)
print(all(EC_genes_reload == XX))

############################################################################################################
# ECs counts:
############################################################################################################
# transform EC_id to new size of the matrix
EC_counts_keep = EC_counts_keep[, keep_EC_matrix]

file_name = file.path("alevin-fry", sample_ids[i], "alevin/geqc_counts.mtx")
writeMM(EC_counts_keep, file = file_name)

EC_counts_reload = readMM(file_name)

# OK, same sizer and content:
dim(EC_counts_reload); dim(EC_counts_keep)
print(all(EC_counts_keep == EC_counts_reload))

print(i)
}
```

# salmon folder
The scripts to generate this simulated data can be found [here](https://github.com/csoneson/differential_regulation_simulation).
The full simulation is used in the mauscript, while here (for space reasons) we used the smaller subset simulation, bases on chromosome 22 only.
