MAVEQC

A R package of quality control on SGE data

Table of Contents

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1. Dependencies
2. Installation
3. File Format
4. Import Data
5. Plasmid QC
   • QC 1: Sample QC
   • Report
6. Screen QC
   • QC 1: Sample QC
   • QC 2: Experiment QC
   • Report
7. Others
   • Pandoc
   • Test datasets
   • Conda

Dependencies

install.packages("configr", version = '0.3.5')
install.packages("vroom", version = '1.6.3')
install.packages("data.table", version = '1.14.8')
install.packages("Ckmeans.1d.dp", version = '4.3.5')
install.packages("gplots", version = '3.1.3')
install.packages("ggplot2", version = '3.4.3')
install.packages("plotly", version = '4.10.4')
install.packages("ggcorrplot", version = '0.1.4.1')
install.packages("corrplot", version = '0.92')
install.packages("see", version = '0.8.0')
install.packages("ggbeeswarm", version = '0.7.2')
install.packages("reactable", version = '0.4.4')
install.packages("reshape2", version = '1.4.4')
install.packages("htmltools", version = '0.5.6')
install.packages("sparkline", version = '2.0')
install.packages("dendextend", version = '1.17.1')
install.packages("gtools", version = '3.9.4')

install.packages("BiocManager")
BiocManager::install(version = "3.18")
BiocManager::install("DESeq2")
BiocManager::install("DEGreport")
BiocManager::install("apeglm")

Load dependencies if required

library(configr)
library(vroom)
library(data.table)
library(Ckmeans.1d.dp)
library(gplots)
library(ggplot2)
library(plotly)
library(ggcorrplot)
library(corrplot)
library(see)
library(ggbeeswarm)
library(reactable)
library(htmltools)
library(sparkline)
library(dendextend)
library(reshape2)
library(gtools)

library(DESeq2)
library(DEGreport)
library(apeglm)

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Installation

Install from github

install.packages("devtools")

library(devtools)
install_github("wtsi-hgi/MAVEQC")

Or

Install from the compiled source file

install.packages("/path/of/MAVEQC.tar.gz", type = "source")

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File Format

sample sheet -- tsv

sample_name	replicate	condition	ref_time_point	library_independent_count	library_dependent_count	valiant_meta	vep_anno	adapt5	adapt3	per_r1_adaptor	per_r2_adaptor	library_name	library_type
sample1	R1	D4	D4	s1.allcounts.tsv.gz	s1.libcounts.tsv.gz	meta.csv.gz	meta_consequences.tsv.gz	CTGACTGGCACCTCTTCCCCCAGGA	CCCCGACCCCTCCCCAGCGTGAATG	0.21	0.10	libA	screen
sample2	R2	D4	D4	s2.allcounts.tsv.gz	s2.libcounts.tsv.gz	meta.csv.gz	meta_consequences.tsv.gz	CTGACTGGCACCTCTTCCCCCAGGA	CCCCGACCCCTCCCCAGCGTGAATG	0.11	0.02	libA	screen
sample3	R3	D4	D4	s3.allcounts.tsv.gz	s3.libcounts.tsv.gz	meta.csv.gz	meta_consequences.tsv.gz	CTGACTGGCACCTCTTCCCCCAGGA	CCCCGACCCCTCCCCAGCGTGAATG	0.01	0.18	libA	screen
sample4	R1	D7	D4	s4.allcounts.tsv.gz	s4.libcounts.tsv.gz	meta.csv.gz	meta_consequences.tsv.gz	CTGACTGGCACCTCTTCCCCCAGGA	CCCCGACCCCTCCCCAGCGTGAATG	0.21	0.10	libA	screen
sample5	R2	D7	D4	s5.allcounts.tsv.gz	s5.libcounts.tsv.gz	meta.csv.gz	meta_consequences.tsv.gz	CTGACTGGCACCTCTTCCCCCAGGA	CCCCGACCCCTCCCCAGCGTGAATG	0.11	0.02	libA	screen
sample6	R3	D7	D4	s6.allcounts.tsv.gz	s6.libcounts.tsv.gz	meta.csv.gz	meta_consequences.tsv.gz	CTGACTGGCACCTCTTCCCCCAGGA	CCCCGACCCCTCCCCAGCGTGAATG	0.01	0.18	libA	screen

• please use the same headers in the example
• replicate, condition and ref_time_point are optional, but required for screen qc
• adapt5 and adapt3 are optional, please leave them blank if you don't have them, but required for reads with primers
• vep_anno, library_name and library_type are not necessary, leave them blank if not available

library dependent counts -- tsv or tsv.gz

ID	NAME	SEQUENCE	LENGTH	COUNT	UNIQUE	SAMPLE
id1	name1	ACTTTTCT	276	32	1	sample1
id2	name2	ATCTTTCT	275	132	0	sample1
id3	name3	ATTCTTCT	275	2	1	sample1

• please use the same headers in the example
• please make sure library dependent sequences match with valiant meta file
• please refer to pyQUEST

library independent counts -- tsv or tsv.gz

SEQUENCE	LENGTH	COUNT
ACTTTTCT	276	32
ATCTTTCT	275	132
ATTCTTCT	275	2

• please use the same headers in the example
• please refer to pyQUEST

valiant meta file

Please use the VaLiAnT output file, refer to VaLiAnT

vep annotation file

Please use one to one mapping file

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Import Data

Import a group of samples from a directory

All the files are in the same directory including library dependent counts, library independent counts, valiant meta csv, vep annotation and the sample sheet.

library(MAVEQC)

sge_objs <- import_sge_files("/path/to/input/directory", "sample_sheet.tsv")

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Plasmid QC

Test datasets are not available now, will add them soon

QC 1: Sample QC

output_dir <- "/path/to/output/directory"

samqc <- create_sampleqc_object(sge_objs)
samqc <- run_sample_qc(samqc, "plasmid")

qcplot_samqc_all(samqc, qc_type = "plasmid", plot_dir = output_dir)
qcout_samqc_all(samqc, qc_type = "plasmid", out_dir = output_dir)

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Report

This creates a html report concatenating all the results including figures and tables. Please make sure you have generated all the figures and tables, otherwise the report may be incomplete.

create_qc_reports("/path/to/sample/sheet", "plasmid", output_dir)

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Screen QC

QC 1: Sample QC

Reference samples must be assigned. MAVEQC automatically creates reference samples (maveqc_ref_time_point and maveqc_ref_time_point_samples) from the sample sheet using ref_time_point and sampe_name.

output_dir <- "/path/to/output/directory"

samqc <- create_sampleqc_object(sge_objs)
samqc <- run_sample_qc(samqc, "screen")

qcplot_samqc_all(samqc, qc_type = "screen", plot_dir = output_dir)
qcout_samqc_all(samqc, qc_type = "screen", out_dir = output_dir)

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QC 2: Experimental QC

MAVEQC automatically creates the coldata (maveqc_deseq_coldata) from sample sheet for Screen QC.

coldata example:

sample_name	replicate	condition
hgsm3_d4_r1	R1	D4
hgsm3_d7_r1	R1	D7
hgsm3_d15_r1	R1	D15
hgsm3_d4_r2	R2	D4
hgsm3_d7_r2	R2	D7
hgsm3_d15_r2	R2	D15
hgsm3_d4_r3	R3	D4
hgsm3_d7_r3	R3	D7
hgsm3_d15_r3	R3	D15

expqc <- create_experimentqc_object(samqc) 
expqc <- run_experiment_qc(expqc) 

qcplot_expqc_all(expqc, plot_dir = output_dir)
qcout_expqc_all(expqc, out_dir = output_dir)

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Report

This creates a html report concatenating all the results including figures and tables. Please make sure you have generated all the figures and tables, otherwise the report may be incomplete.

create_qc_reports("/path/to/sample/sheet", "screen", output_dir)

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Others

Pandoc

Pandoc is required to generate the R markdown report. Please download and install it from https://pandoc.org/installing.html

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apeglm

the version of apeglm must be >= 1.22.1, optimHess problem in the lower version like below.

Error in optimHess(par = init, fn = nbinomFn, gr = nbinomGr, x = x, y = y,  : 
non-finite value supplied by optim

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Conda

When installing DESeq2, it may have error (Rlog1) on Mac M1 chip. Try cmd below to fix it.

export PKG_CPPFLAGS="-DHAVE_WORKING_LOG1P"

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