Skip to content

A collection of custom scripts used in the placenta transcriptome paper, Gong et al. Nat Comm, 2021

License

Notifications You must be signed in to change notification settings

sung/POPS-Placenta-Transcriptome-2020

Repository files navigation

License: MIT GitHub release GitHub all releases GitHub last commit

Introduction

This is a collection of custom scripts used for the following paper: "The RNA landscape of the human placenta in health and disease, Gong et al. 2021. Nat Comm, 2021". A Shiny app to browse the placenta transcriptome is also available and the source code is here.

Initial mapping of RNA-Seq data

The RNA-Seq reads were trimmed (using cutadapt and Trim Galore!) and mapped to the primary chromosomal assemblies of the GRCh38.p3 version of the human reference genome using TopHat2, a splice-aware mapper built on top of Bowtie2 short-read aligner. For more details, read Gong et al., Epigenetics, 2018 and Gong et al., JCI Insight, 2018.

SessionInfo() shown below (or here)

R version 3.6.1 (2019-07-05)
Platform: x86_64-pc-linux-gnu (64-bit)
Running under: Scientific Linux 7.8 (Nitrogen)

Matrix products: default
BLAS:   /usr/local/software/spack/spack-0.11.2/opt/spack/linux-rhel7-x86_64/gcc-5.4.0/r-3.6.1-zrytncqvsnw5h4dl6t6njefj7otl4bg4/rlib/R/lib/libRblas.so
LAPACK: /usr/local/software/spack/spack-0.11.2/opt/spack/linux-rhel7-x86_64/gcc-5.4.0/r-3.6.1-zrytncqvsnw5h4dl6t6njefj7otl4bg4/rlib/R/lib/libRlapack.so

locale:
 [1] LC_CTYPE=en_GB.UTF-8       LC_NUMERIC=C               LC_TIME=en_GB.UTF-8        LC_COLLATE=en_GB.UTF-8    
 [5] LC_MONETARY=en_GB.UTF-8    LC_MESSAGES=en_GB.UTF-8    LC_PAPER=en_GB.UTF-8       LC_NAME=C                 
 [9] LC_ADDRESS=C               LC_TELEPHONE=C             LC_MEASUREMENT=en_GB.UTF-8 LC_IDENTIFICATION=C       

attached base packages:
[1] parallel  stats4    stats     graphics  grDevices utils     datasets  methods   base     

other attached packages:
 [1] scales_1.1.0         ggthemes_4.2.0       GenomicRanges_1.38.0 GenomeInfoDb_1.22.0  IRanges_2.20.2      
 [6] S4Vectors_0.24.3     BiocGenerics_0.32.0  ggplot2_3.2.1        RColorBrewer_1.1-2   nvimcom_0.9-83      
[11] data.table_1.12.8    colorout_1.2-2      

loaded via a namespace (and not attached):
 [1] Rcpp_1.0.3             pillar_1.4.3           compiler_3.6.1         XVector_0.26.0         bitops_1.0-6          
 [6] tools_3.6.1            zlibbioc_1.32.0        lifecycle_0.1.0        tibble_2.1.3           gtable_0.3.0          
[11] pkgconfig_2.0.3        rlang_0.4.4            GenomeInfoDbData_1.2.2 withr_2.1.2            dplyr_0.8.4           
[16] stringr_1.4.0          grid_3.6.1             tidyselect_1.0.0       glue_1.3.1             R6_2.4.1              
[21] purrr_0.3.3            magrittr_1.5           assertthat_0.2.1       colorspace_1.4-1       stringi_1.4.5         
[26] RCurl_1.98-1.1         lazyeval_0.2.2         munsell_0.5.0          crayon_1.3.4          

Contacts