1 Introduction

The BCalm package provides a framework for analyzing data from Massively Parallel Reporter Assays (MPRA) and is built on top of the mpra package. BCalm adapts the existing mpralm method but enhances it by modeling individual barcode counts rather than aggregating counts per sequence. Furthermore, the package includes a set of pre-processing functions and plotting capabilities, facilitating the visualization and interpretation of results. BCalm is more robust to outlier MPRA counts. Variant and element analysis are both shown below together with a significance test of elements against a control group (e.g. negative controls).

1.1 Citing BCalm

The BCalm package is still unpublished, citing details will be provided later. When using BCalm, please cite the mpra package (Myint et al. 2019) and the limma-voom framework (Law et al. 2014).

1.2 Additional information for the installation

The package is currently available on GitHub and can be installed using remotes (Csárdi et al. 2024) or devtools (Wickham et al. 2022). The package requires R >= 3.5, <= 4.4.0. If you have any trouble with the provided package feel free to let us know by creating an issue directly in the BCalm GitHub repository. To display the vignette correctly, the kableExtra and ggplot2 packages are required.

2 Preprocessing data

The first dataframe contains as small subset of a lentiMPRA dataset performed within HepG2 cells with three technical replicates (IGVF accession identifier: IGVFSM9009DVDG). Sequences tested in this experiment aim to capture variant effects across tens of thousands of candidate cis-regulatory element (cCRE) sequences of 200 base pair (bp) length. The input files used here were obtained from MPRAsnakeflow, a Snakemake workflow produced as part of the Impact of Genomic Variation on Function (IGVF) Consortium. MPRAsnakeflow is a comprehensive pipeline which performs both the assignment of barcodes to the designed oligos and the preparation of count tables of DNA and RNA counts based on the observed number of barcodes within the targeted DNA and RNA sequencing (modified from (Gordon et al. 2020)).

data("BcSetExample")
nr_reps = 3
# show the data
kable(head(BcSetExample), "html") %>% kable_styling("striped") %>% scroll_box(width = "100%")

Barcode	name	dna_count_1	rna_count_1	dna_count_2	rna_count_2	dna_count_3	rna_count_3
AAAAAAAAAAGCTGC	oligo_006364	11	10	8	6	1	3
AAAAAAAAATCACAG	oligo_005641	8	7	1	2	1	29
AAAAAAAAATTGAGC	oligo_005719	2	25	2	88	1	30
AAAAAAAAATTGTAT	oligo_005725	4	12	4	2	2	6
AAAAAAAACACATGA	oligo_005412	21	15	5	12	11	51
AAAAAAAACATAGTT	oligo_006471	8	3	3	5	7	3

In general, any sequence can be tested using an MPRA. Possible analyses can be differentiated by whether they compare the activity of different conditions of the same region, such as variant testing, or whether they compare the activities of different regions. For element testing, the tested sequences in this vignette are compared to a group of negative control sequences (known to have low activity in HepG2) and the sequences to be tested. We show the usage of BCalm on a variant dataset as well as an element dataset in this vignette. First, we show how to correctly preprocess the data.

2.1 Variant testing

To prepare data for variant testing, we use the create_var_df function from BCalm. This function requires a mapping dataframe with information linking each reference allele to its corresponding alternative allele. Here, we use MapExample, a dataframe containing three essential columns: ID, REF, and ALT. This setup provides the necessary reference and alternative allele data to enable variant analysis.

# load the variant map
data("MapExample")
# show the data
kable(head(MapExample), "html") %>% kable_styling("striped") %>% scroll_box(width = "100%")

ID	REF	ALT
variant_1	oligo_005868	oligo_005870
variant_2	oligo_005299	oligo_005300
variant_3	oligo_006685	oligo_006687
variant_4	oligo_006919	oligo_006920
variant_5	oligo_006895	oligo_006897
variant_6	oligo_006675	oligo_006677

# create the variant dataframe by adding the variant ID to the DNA and RNA counts
var_df <- create_var_df(BcSetExample, MapExample)
# show the data
kable(head(var_df), "html") %>% kable_styling("striped") %>% scroll_box(width = "100%")

variant_id	allele	Barcode	dna_count_1	rna_count_1	dna_count_2	rna_count_2	dna_count_3	rna_count_3
variant_820	ref	TCTTAAGTAAGAAGG	2	3	1	2	9	15
variant_820	ref	GTAAGAATGGTTGGG	7	1	2	10	7	5
variant_820	ref	TTTAGAAGTACACTC	4	3	4	11	1	1
variant_820	ref	TTCGTTTTGACTAGG	4	4	9	11	6	14
variant_820	ref	TCCGTACATCGTGAA	1	2	2	2	1	4
variant_820	ref	GGTTCAAGGAATACC	1	7	2	4	3	1

Optionally, downsampling can be performed to our dataframe var_df now. The function downsample_barcodes allows users to reduce the number of barcodes while retaining a representative subset. This way, the number of barcodes of oligos with many barcodes are reduced, which simplifies the data handling and reduces the sparseness of the data table (i.e. increased speed and reduced memory requirements). The degree of downsampling can be controlled by adjusting the sampling rate, which is expressed as a percentile value percentile, with a default of 0.975. The id_column_name argument specifies the column in the input data frame that contains the unique identifiers for each variant (here variant_id).

var_df <- downsample_barcodes(var_df, id_column_name="variant_id")

After downsampling the barcode counts in our dataset, we can prepare the data for analysis using the create_dna_df and create_rna_df functions. Only six rows are shown here (original size of the dataframe 996 × 474).

dna_var <- create_dna_df(var_df)
kable(head(dna_var), "html") %>% kable_styling("striped") %>% scroll_box(width = "100%")

	sample_count_1_bc1_ref	sample_count_1_bc2_ref	sample_count_1_bc3_ref	sample_count_1_bc4_ref	sample_count_1_bc5_ref	sample_count_1_bc6_ref	sample_count_1_bc7_ref	sample_count_1_bc8_ref	sample_count_1_bc9_ref	sample_count_1_bc10_ref	sample_count_1_bc11_ref	sample_count_1_bc12_ref	sample_count_1_bc13_ref	sample_count_1_bc14_ref	sample_count_1_bc15_ref	sample_count_1_bc16_ref	sample_count_1_bc17_ref	sample_count_1_bc18_ref	sample_count_1_bc19_ref	sample_count_1_bc20_ref	sample_count_1_bc21_ref	sample_count_1_bc22_ref	sample_count_1_bc23_ref	sample_count_1_bc24_ref	sample_count_1_bc25_ref	sample_count_1_bc26_ref	sample_count_1_bc27_ref	sample_count_1_bc28_ref	sample_count_1_bc29_ref	sample_count_1_bc30_ref	sample_count_1_bc31_ref	sample_count_1_bc32_ref	sample_count_1_bc33_ref	sample_count_1_bc34_ref	sample_count_1_bc35_ref	sample_count_1_bc36_ref	sample_count_1_bc37_ref	sample_count_1_bc38_ref	sample_count_1_bc39_ref	sample_count_1_bc40_ref	sample_count_1_bc41_ref	sample_count_1_bc42_ref	sample_count_1_bc43_ref	sample_count_1_bc44_ref	sample_count_1_bc45_ref	sample_count_1_bc46_ref	sample_count_1_bc47_ref	sample_count_1_bc48_ref	sample_count_1_bc49_ref	sample_count_1_bc50_ref	sample_count_1_bc51_ref	sample_count_1_bc52_ref	sample_count_1_bc53_ref	sample_count_1_bc54_ref	sample_count_1_bc55_ref	sample_count_1_bc56_ref	sample_count_1_bc57_ref	sample_count_1_bc58_ref	sample_count_1_bc59_ref	sample_count_1_bc60_ref	sample_count_1_bc61_ref	sample_count_1_bc62_ref	sample_count_1_bc63_ref	sample_count_1_bc64_ref	sample_count_1_bc65_ref	sample_count_1_bc66_ref	sample_count_1_bc67_ref	sample_count_1_bc68_ref	sample_count_1_bc69_ref	sample_count_1_bc70_ref	sample_count_1_bc71_ref	sample_count_1_bc72_ref	sample_count_1_bc73_ref	sample_count_1_bc74_ref	sample_count_1_bc75_ref	sample_count_1_bc76_ref	sample_count_1_bc77_ref	sample_count_1_bc78_ref	sample_count_1_bc79_ref	sample_count_1_bc1_alt	sample_count_1_bc2_alt	sample_count_1_bc3_alt	sample_count_1_bc4_alt	sample_count_1_bc5_alt	sample_count_1_bc6_alt	sample_count_1_bc7_alt	sample_count_1_bc8_alt	sample_count_1_bc9_alt	sample_count_1_bc10_alt	sample_count_1_bc11_alt	sample_count_1_bc12_alt	sample_count_1_bc13_alt	sample_count_1_bc14_alt	sample_count_1_bc15_alt	sample_count_1_bc16_alt	sample_count_1_bc17_alt	sample_count_1_bc18_alt	sample_count_1_bc19_alt	sample_count_1_bc20_alt	sample_count_1_bc21_alt	sample_count_1_bc22_alt	sample_count_1_bc23_alt	sample_count_1_bc24_alt	sample_count_1_bc25_alt	sample_count_1_bc26_alt	sample_count_1_bc27_alt	sample_count_1_bc28_alt	sample_count_1_bc29_alt	sample_count_1_bc30_alt	sample_count_1_bc31_alt	sample_count_1_bc32_alt	sample_count_1_bc33_alt	sample_count_1_bc34_alt	sample_count_1_bc35_alt	sample_count_1_bc36_alt	sample_count_1_bc37_alt	sample_count_1_bc38_alt	sample_count_1_bc39_alt	sample_count_1_bc40_alt	sample_count_1_bc41_alt	sample_count_1_bc42_alt	sample_count_1_bc43_alt	sample_count_1_bc44_alt	sample_count_1_bc45_alt	sample_count_1_bc46_alt	sample_count_1_bc47_alt	sample_count_1_bc48_alt	sample_count_1_bc49_alt	sample_count_1_bc50_alt	sample_count_1_bc51_alt	sample_count_1_bc52_alt	sample_count_1_bc53_alt	sample_count_1_bc54_alt	sample_count_1_bc55_alt	sample_count_1_bc56_alt	sample_count_1_bc57_alt	sample_count_1_bc58_alt	sample_count_1_bc59_alt	sample_count_1_bc60_alt	sample_count_1_bc61_alt	sample_count_1_bc62_alt	sample_count_1_bc63_alt	sample_count_1_bc64_alt	sample_count_1_bc65_alt	sample_count_1_bc66_alt	sample_count_1_bc67_alt	sample_count_1_bc68_alt	sample_count_1_bc69_alt	sample_count_1_bc70_alt	sample_count_1_bc71_alt	sample_count_1_bc72_alt	sample_count_1_bc73_alt	sample_count_1_bc74_alt	sample_count_1_bc75_alt	sample_count_1_bc76_alt	sample_count_1_bc77_alt	sample_count_1_bc78_alt	sample_count_1_bc79_alt	sample_count_2_bc1_ref	sample_count_2_bc2_ref	sample_count_2_bc3_ref	sample_count_2_bc4_ref	sample_count_2_bc5_ref	sample_count_2_bc6_ref	sample_count_2_bc7_ref	sample_count_2_bc8_ref	sample_count_2_bc9_ref	sample_count_2_bc10_ref	sample_count_2_bc11_ref	sample_count_2_bc12_ref	sample_count_2_bc13_ref	sample_count_2_bc14_ref	sample_count_2_bc15_ref	sample_count_2_bc16_ref	sample_count_2_bc17_ref	sample_count_2_bc18_ref	sample_count_2_bc19_ref	sample_count_2_bc20_ref	sample_count_2_bc21_ref	sample_count_2_bc22_ref	sample_count_2_bc23_ref	sample_count_2_bc24_ref	sample_count_2_bc25_ref	sample_count_2_bc26_ref	sample_count_2_bc27_ref	sample_count_2_bc28_ref	sample_count_2_bc29_ref	sample_count_2_bc30_ref	sample_count_2_bc31_ref	sample_count_2_bc32_ref	sample_count_2_bc33_ref	sample_count_2_bc34_ref	sample_count_2_bc35_ref	sample_count_2_bc36_ref	sample_count_2_bc37_ref	sample_count_2_bc38_ref	sample_count_2_bc39_ref	sample_count_2_bc40_ref	sample_count_2_bc41_ref	sample_count_2_bc42_ref	sample_count_2_bc43_ref	sample_count_2_bc44_ref	sample_count_2_bc45_ref	sample_count_2_bc46_ref	sample_count_2_bc47_ref	sample_count_2_bc48_ref	sample_count_2_bc49_ref	sample_count_2_bc50_ref	sample_count_2_bc51_ref	sample_cou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lt	sample_count_3_bc25_alt	sample_count_3_bc26_alt	sample_count_3_bc27_alt	sample_count_3_bc28_alt	sample_count_3_bc29_alt	sample_count_3_bc30_alt	sample_count_3_bc31_alt	sample_count_3_bc32_alt	sample_count_3_bc33_alt	sample_count_3_bc34_alt	sample_count_3_bc35_alt	sample_count_3_bc36_alt	sample_count_3_bc37_alt	sample_count_3_bc38_alt	sample_count_3_bc39_alt	sample_count_3_bc40_alt	sample_count_3_bc41_alt	sample_count_3_bc42_alt	sample_count_3_bc43_alt	sample_count_3_bc44_alt	sample_count_3_bc45_alt	sample_count_3_bc46_alt	sample_count_3_bc47_alt	sample_count_3_bc48_alt	sample_count_3_bc49_alt	sample_count_3_bc50_alt	sample_count_3_bc51_alt	sample_count_3_bc52_alt	sample_count_3_bc53_alt	sample_count_3_bc54_alt	sample_count_3_bc55_alt	sample_count_3_bc56_alt	sample_count_3_bc57_alt	sample_count_3_bc58_alt	sample_count_3_bc59_alt	sample_count_3_bc60_alt	sample_count_3_bc61_alt	sample_count_3_bc62_alt	sample_count_3_bc63_alt	sample_count_3_bc64_alt	sample_count_3_bc65_alt	sample_count_3_bc66_alt	sample_count_3_bc67_alt	sample_count_3_bc68_alt	sample_count_3_bc69_alt	sample_count_3_bc70_alt	sample_count_3_bc71_alt	sample_count_3_bc72_alt	sample_count_3_bc73_alt	sample_count_3_bc74_alt	sample_count_3_bc75_alt	sample_count_3_bc76_alt	sample_count_3_bc77_alt	sample_count_3_bc78_alt	sample_count_3_bc79_alt
variant_10	8	4	2	5	3	8	9	6	2	7	4	3	6	2	5	2	4	4	5	4	1	8	1	1	5	5	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	4	4	7	8	2	1	1	3	1	2	2	4	1	1	2	3	2	1	3	3	1	1	3	5	2	1	3	1	3	7	3	3	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	4	3	1	2	1	1	4	3	4	6	1	1	2	1	7	2	2	4	1	2	3	2	4	2	2	5	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	7	3	1	3	3	6	3	4	4	3	3	2	1	1	1	1	1	1	6	2	5	2	1	3	1	1	4	8	1	6	2	3	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	11	7	3	1	4	4	2	9	2	14	1	7	1	4	2	2	6	3	3	1	1	5	2	3	4	6	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	1	3	7	8	7	1	2	4	5	5	6	6	4	4	2	12	1	6	6	4	1	3	2	1	3	5	4	13	3	6	2	13	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
variant_100	12	11	2	3	2	3	2	11	6	3	19	3	4	4	7	2	4	5	8	3	3	1	3	3	3	5	10	4	6	6	11	2	8	4	4	2	4	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	3	3	10	5	8	3	4	1	6	3	2	4	3	7	9	2	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	2	7	1	4	2	3	4	3	3	3	7	6	2	3	1	12	5	7	6	2	1	4	2	9	2	3	7	3	5	5	12	9	9	3	5	1	1	9	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	4	2	9	7	6	2	3	5	14	5	4	8	5	4	2	2	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	6	7	6	5	2	2	3	3	1	4	5	4	6	10	7	3	4	2	4	1	3	2	2	2	1	7	2	2	1	3	7	4	2	5	1	1	4	3	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	5	2	10	6	1	2	2	1	3	1	8	3	2	1	1	2	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
variant_100314	9	5	1	5	12	2	12	10	10	3	7	16	4	8	2	8	2	4	13	3	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	7	10	4	5	4	3	12	10	5	4	11	17	1	5	5	7	5	5	13	10	4	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	3	1	6	1	5	9	3	3	10	12	9	24	2	1	2	10	3	2	3	14	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
variant_100463	7	8	3	1	1	7	2	3	8	1	6	3	5	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	1	3	3	1	3	3	6	1	3	2	6	1	5	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	4	4	4	2	3	3	1	2	3	6	1	4	4	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
variant_101	18	16	3	9	4	1	4	3	14	5	3	7	1	1	7	5	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	1	2	4	7	7	1	3	3	4	1	6	2	12	2	10	4	1	6	2	6	3	3	1	8	3	1	2	10	4	5	10	6	3	1	3	3	4	5	5	2	5	6	5	11	5	7	3	2	2	3	5	11	13	10	7	2	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	1	13	6	7	2	2	1	1	8	1	3	2	3	6	12	2	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	1	5	1	2	2	16	12	1	10	3	2	2	4	4	9	5	6	1	6	2	3	2	7	2	1	2	6	3	1	2	3	3	1	4	8	1	1	4	4	5	1	4	9	5	4	2	7	9	1	9	11	4	7	12	9	6	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	10	11	2	6	6	1	4	1	2	1	2	3	7	7	6	2	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	7	1	2	8	6	5	5	1	6	5	2	3	3	2	2	3	2	2	3	3	4	5	2	5	2	2	1	5	15	1	5	4	2	1	1	1	4	4	1	2	1	3	14	12	2	1	2	7	2	2	5	8	12	4	7	4	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
variant_101165	2	8	9	7	7	5	5	2	2	21	2	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	3	2	4	3	4	5	3	4	2	10	7	10	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	1	6	2	4	3	2	1	1	7	10	1	3	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA

rna_var <- create_rna_df(var_df)
kable(head(rna_var), "html") %>% kable_styling("striped") %>% scroll_box(width = "100%")

	sample_count_1_bc1_ref	sample_count_1_bc2_ref	sample_count_1_bc3_ref	sample_count_1_bc4_ref	sample_count_1_bc5_ref	sample_count_1_bc6_ref	sample_count_1_bc7_ref	sample_count_1_bc8_ref	sample_count_1_bc9_ref	sample_count_1_bc10_ref	sample_count_1_bc11_ref	sample_count_1_bc12_ref	sample_count_1_bc13_ref	sample_count_1_bc14_ref	sample_count_1_bc15_ref	sample_count_1_bc16_ref	sample_count_1_bc17_ref	sample_count_1_bc18_ref	sample_count_1_bc19_ref	sample_count_1_bc20_ref	sample_count_1_bc21_ref	sample_count_1_bc22_ref	sample_count_1_bc23_ref	sample_count_1_bc24_ref	sample_count_1_bc25_ref	sample_count_1_bc26_ref	sample_count_1_bc27_ref	sample_count_1_bc28_ref	sample_count_1_bc29_ref	sample_count_1_bc30_ref	sample_count_1_bc31_ref	sample_count_1_bc32_ref	sample_count_1_bc33_ref	sample_count_1_bc34_ref	sample_count_1_bc35_ref	sample_count_1_bc36_ref	sample_count_1_bc37_ref	sample_count_1_bc38_ref	sample_count_1_bc39_ref	sample_count_1_bc40_ref	sample_count_1_bc41_ref	sample_count_1_bc42_ref	sample_count_1_bc43_ref	sample_count_1_bc44_ref	sample_count_1_bc45_ref	sample_count_1_bc46_ref	sample_count_1_bc47_ref	sample_count_1_bc48_ref	sample_count_1_bc49_ref	sample_count_1_bc50_ref	sample_count_1_bc51_ref	sample_count_1_bc52_ref	sample_count_1_bc53_ref	sample_count_1_bc54_ref	sample_count_1_bc55_ref	sample_count_1_bc56_ref	sample_count_1_bc57_ref	sample_count_1_bc58_ref	sample_count_1_bc59_ref	sample_count_1_bc60_ref	sample_count_1_bc61_ref	sample_count_1_bc62_ref	sample_count_1_bc63_ref	sample_count_1_bc64_ref	sample_count_1_bc65_ref	sample_count_1_bc66_ref	sample_count_1_bc67_ref	sample_count_1_bc68_ref	sample_count_1_bc69_ref	sample_count_1_bc70_ref	sample_count_1_bc71_ref	sample_count_1_bc72_ref	sample_count_1_bc73_ref	sample_count_1_bc74_ref	sample_count_1_bc75_ref	sample_count_1_bc76_ref	sample_count_1_bc77_ref	sample_count_1_bc78_ref	sample_count_1_bc79_ref	sample_count_1_bc1_alt	sample_count_1_bc2_alt	sample_count_1_bc3_alt	sample_count_1_bc4_alt	sample_count_1_bc5_alt	sample_count_1_bc6_alt	sample_count_1_bc7_alt	sample_count_1_bc8_alt	sample_count_1_bc9_alt	sample_count_1_bc10_alt	sample_count_1_bc11_alt	sample_count_1_bc12_alt	sample_count_1_bc13_alt	sample_count_1_bc14_alt	sample_count_1_bc15_alt	sample_count_1_bc16_alt	sample_count_1_bc17_alt	sample_count_1_bc18_alt	sample_count_1_bc19_alt	sample_count_1_bc20_alt	sample_count_1_bc21_alt	sample_count_1_bc22_alt	sample_count_1_bc23_alt	sample_count_1_bc24_alt	sample_count_1_bc25_alt	sample_count_1_bc26_alt	sample_count_1_bc27_alt	sample_count_1_bc28_alt	sample_count_1_bc29_alt	sample_count_1_bc30_alt	sample_count_1_bc31_alt	sample_count_1_bc32_alt	sample_count_1_bc33_alt	sample_count_1_bc34_alt	sample_count_1_bc35_alt	sample_count_1_bc36_alt	sample_count_1_bc37_alt	sample_count_1_bc38_alt	sample_count_1_bc39_alt	sample_count_1_bc40_alt	sample_count_1_bc41_alt	sample_count_1_bc42_alt	sample_count_1_bc43_alt	sample_count_1_bc44_alt	sample_count_1_bc45_alt	sample_count_1_bc46_alt	sample_count_1_bc47_alt	sample_count_1_bc48_alt	sample_count_1_bc49_alt	sample_count_1_bc50_alt	sample_count_1_bc51_alt	sample_count_1_bc52_alt	sample_count_1_bc53_alt	sample_count_1_bc54_alt	sample_count_1_bc55_alt	sample_count_1_bc56_alt	sample_count_1_bc57_alt	sample_count_1_bc58_alt	sample_count_1_bc59_alt	sample_count_1_bc60_alt	sample_count_1_bc61_alt	sample_count_1_bc62_alt	sample_count_1_bc63_alt	sample_count_1_bc64_alt	sample_count_1_bc65_alt	sample_count_1_bc66_alt	sample_count_1_bc67_alt	sample_count_1_bc68_alt	sample_count_1_bc69_alt	sample_count_1_bc70_alt	sample_count_1_bc71_alt	sample_count_1_bc72_alt	sample_count_1_bc73_alt	sample_count_1_bc74_alt	sample_count_1_bc75_alt	sample_count_1_bc76_alt	sample_count_1_bc77_alt	sample_count_1_bc78_alt	sample_count_1_bc79_alt	sample_count_2_bc1_ref	sample_count_2_bc2_ref	sample_count_2_bc3_ref	sample_count_2_bc4_ref	sample_count_2_bc5_ref	sample_count_2_bc6_ref	sample_count_2_bc7_ref	sample_count_2_bc8_ref	sample_count_2_bc9_ref	sample_count_2_bc10_ref	sample_count_2_bc11_ref	sample_count_2_bc12_ref	sample_count_2_bc13_ref	sample_count_2_bc14_ref	sample_count_2_bc15_ref	sample_count_2_bc16_ref	sample_count_2_bc17_ref	sample_count_2_bc18_ref	sample_count_2_bc19_ref	sample_count_2_bc20_ref	sample_count_2_bc21_ref	sample_count_2_bc22_ref	sample_count_2_bc23_ref	sample_count_2_bc24_ref	sample_count_2_bc25_ref	sample_count_2_bc26_ref	sample_count_2_bc27_ref	sample_count_2_bc28_ref	sample_count_2_bc29_ref	sample_count_2_bc30_ref	sample_count_2_bc31_ref	sample_count_2_bc32_ref	sample_count_2_bc33_ref	sample_count_2_bc34_ref	sample_count_2_bc35_ref	sample_count_2_bc36_ref	sample_count_2_bc37_ref	sample_count_2_bc38_ref	sample_count_2_bc39_ref	sample_count_2_bc40_ref	sample_count_2_bc41_ref	sample_count_2_bc42_ref	sample_count_2_bc43_ref	sample_count_2_bc44_ref	sample_count_2_bc45_ref	sample_count_2_bc46_ref	sample_count_2_bc47_ref	sample_count_2_bc48_ref	sample_count_2_bc49_ref	sample_count_2_bc50_ref	sample_count_2_bc51_ref	sample_count_2_bc52_ref	sample_count_2_bc53_ref	sample_count_2_bc54_ref	sample_count_2_bc55_ref	sample_count_2_bc56_ref	sample_count_2_bc57_ref	sample_count_2_bc58_ref	sample_count_2_bc59_ref	sample_count_2_bc60_ref	sample_count_2_bc61_ref	sample_count_2_bc62_ref	sample_count_2_bc63_ref	sample_count_2_bc64_ref	sample_count_2_bc65_ref	sample_count_2_bc66_ref	sample_count_2_bc67_ref	sample_count_2_bc68_ref	sample_count_2_bc69_ref	sample_count_2_bc70_ref	sample_count_2_bc71_ref	sample_count_2_bc72_ref	sample_count_2_bc73_ref	sample_count_2_bc74_ref	sample_count_2_bc75_ref	sample_count_2_bc76_ref	sample_count_2_bc77_ref	sample_count_2_bc78_ref	sample_count_2_bc79_ref	sample_count_2_bc1_alt	sample_count_2_bc2_alt	sample_count_2_bc3_alt	sample_count_2_bc4_alt	sample_count_2_bc5_alt	sample_count_2_bc6_alt	sample_count_2_bc7_alt	sample_count_2_bc8_alt	sample_count_2_bc9_alt	sample_count_2_bc10_alt	sample_count_2_bc11_alt	sample_count_2_bc12_alt	sample_count_2_bc13_alt	sample_count_2_bc14_alt	sample_count_2_bc15_alt	sample_count_2_bc16_alt	sample_count_2_bc17_alt	sample_count_2_bc18_alt	sample_count_2_bc19_alt	sample_count_2_bc20_alt	sample_count_2_bc21_alt	sample_count_2_bc22_alt	sample_count_2_bc23_alt	sample_count_2_bc24_alt	sample_count_2_bc25_alt	sample_count_2_bc26_alt	sample_count_2_bc27_alt	sample_count_2_bc28_alt	sample_count_2_bc29_alt	sample_count_2_bc30_alt	sample_count_2_bc31_alt	sample_count_2_bc32_alt	sample_count_2_bc33_alt	sample_count_2_bc34_alt	sample_count_2_bc35_alt	sample_count_2_bc36_alt	sample_count_2_bc37_alt	sample_count_2_bc38_alt	sample_count_2_bc39_alt	sample_count_2_bc40_alt	sample_count_2_bc41_alt	sample_count_2_bc42_alt	sample_count_2_bc43_alt	sample_count_2_bc44_alt	sample_count_2_bc45_alt	sample_count_2_bc46_alt	sample_count_2_bc47_alt	sample_count_2_bc48_alt	sample_count_2_bc49_alt	sample_count_2_bc50_alt	sample_count_2_bc51_alt	sample_count_2_bc52_alt	sample_count_2_bc53_alt	sample_count_2_bc54_alt	sample_count_2_bc55_alt	sample_count_2_bc56_alt	sample_count_2_bc57_alt	sample_count_2_bc58_alt	sample_count_2_bc59_alt	sample_count_2_bc60_alt	sample_count_2_bc61_alt	sample_count_2_bc62_alt	sample_count_2_bc63_alt	sample_count_2_bc64_alt	sample_count_2_bc65_alt	sample_count_2_bc66_alt	sample_count_2_bc67_alt	sample_count_2_bc68_alt	sample_count_2_bc69_alt	sample_count_2_bc70_alt	sample_count_2_bc71_alt	sample_count_2_bc72_alt	sample_count_2_bc73_alt	sample_count_2_bc74_alt	sample_count_2_bc75_alt	sample_count_2_bc76_alt	sample_count_2_bc77_alt	sample_count_2_bc78_alt	sample_count_2_bc79_alt	sample_count_3_bc1_ref	sample_count_3_bc2_ref	sample_count_3_bc3_ref	sample_count_3_bc4_ref	sample_count_3_bc5_ref	sample_count_3_bc6_ref	sample_count_3_bc7_ref	sample_count_3_bc8_ref	sample_count_3_bc9_ref	sample_count_3_bc10_ref	sample_count_3_bc11_ref	sample_count_3_bc12_ref	sample_count_3_bc13_ref	sample_count_3_bc14_ref	sample_count_3_bc15_ref	sample_count_3_bc16_ref	sample_count_3_bc17_ref	sample_count_3_bc18_ref	sample_count_3_bc19_ref	sample_count_3_bc20_ref	sample_count_3_bc21_ref	sample_count_3_bc22_ref	sample_count_3_bc23_ref	sample_count_3_bc24_ref	sample_count_3_bc25_ref	sample_count_3_bc26_ref	sample_count_3_bc27_ref	sample_count_3_bc28_ref	sample_count_3_bc29_ref	sample_count_3_bc30_ref	sample_count_3_bc31_ref	sample_count_3_bc32_ref	sample_count_3_bc33_ref	sample_count_3_bc34_ref	sample_count_3_bc35_ref	sample_count_3_bc36_ref	sample_count_3_bc37_ref	sample_count_3_bc38_ref	sample_count_3_bc39_ref	sample_count_3_bc40_ref	sample_count_3_bc41_ref	sample_count_3_bc42_ref	sample_count_3_bc43_ref	sample_count_3_bc44_ref	sample_count_3_bc45_ref	sample_count_3_bc46_ref	sample_count_3_bc47_ref	sample_count_3_bc48_ref	sample_count_3_bc49_ref	sample_count_3_bc50_ref	sample_count_3_bc51_ref	sample_count_3_bc52_ref	sample_count_3_bc53_ref	sample_count_3_bc54_ref	sample_count_3_bc55_ref	sample_count_3_bc56_ref	sample_count_3_bc57_ref	sample_count_3_bc58_ref	sample_count_3_bc59_ref	sample_count_3_bc60_ref	sample_count_3_bc61_ref	sample_count_3_bc62_ref	sample_count_3_bc63_ref	sample_count_3_bc64_ref	sample_count_3_bc65_ref	sample_count_3_bc66_ref	sample_count_3_bc67_ref	sample_count_3_bc68_ref	sample_count_3_bc69_ref	sample_count_3_bc70_ref	sample_count_3_bc71_ref	sample_count_3_bc72_ref	sample_count_3_bc73_ref	sample_count_3_bc74_ref	sample_count_3_bc75_ref	sample_count_3_bc76_ref	sample_count_3_bc77_ref	sample_count_3_bc78_ref	sample_count_3_bc79_ref	sample_count_3_bc1_alt	sample_count_3_bc2_alt	sample_count_3_bc3_alt	sample_count_3_bc4_alt	sample_count_3_bc5_alt	sample_count_3_bc6_alt	sample_count_3_bc7_alt	sample_count_3_bc8_alt	sample_count_3_bc9_alt	sample_count_3_bc10_alt	sample_count_3_bc11_alt	sample_count_3_bc12_alt	sample_count_3_bc13_alt	sample_count_3_bc14_alt	sample_count_3_bc15_alt	sample_count_3_bc16_alt	sample_count_3_bc17_alt	sample_count_3_bc18_alt	sample_count_3_bc19_alt	sample_count_3_bc20_alt	sample_count_3_bc21_alt	sample_count_3_bc22_alt	sample_count_3_bc23_alt	sample_count_3_bc24_alt	sample_count_3_bc25_alt	sample_count_3_bc26_alt	sample_count_3_bc27_alt	sample_count_3_bc28_alt	sample_count_3_bc29_alt	sample_count_3_bc30_alt	sample_count_3_bc31_alt	sample_count_3_bc32_alt	sample_count_3_bc33_alt	sample_count_3_bc34_alt	sample_count_3_bc35_alt	sample_count_3_bc36_alt	sample_count_3_bc37_alt	sample_count_3_bc38_alt	sample_count_3_bc39_alt	sample_count_3_bc40_alt	sample_count_3_bc41_alt	sample_count_3_bc42_alt	sample_count_3_bc43_alt	sample_count_3_bc44_alt	sample_count_3_bc45_alt	sample_count_3_bc46_alt	sample_count_3_bc47_alt	sample_count_3_bc48_alt	sample_count_3_bc49_alt	sample_count_3_bc50_alt	sample_count_3_bc51_alt	sample_count_3_bc52_alt	sample_count_3_bc53_alt	sample_count_3_bc54_alt	sample_count_3_bc55_alt	sample_count_3_bc56_alt	sample_count_3_bc57_alt	sample_count_3_bc58_alt	sample_count_3_bc59_alt	sample_count_3_bc60_alt	sample_count_3_bc61_alt	sample_count_3_bc62_alt	sample_count_3_bc63_alt	sample_count_3_bc64_alt	sample_count_3_bc65_alt	sample_count_3_bc66_alt	sample_count_3_bc67_alt	sample_count_3_bc68_alt	sample_count_3_bc69_alt	sample_count_3_bc70_alt	sample_count_3_bc71_alt	sample_count_3_bc72_alt	sample_count_3_bc73_alt	sample_count_3_bc74_alt	sample_count_3_bc75_alt	sample_count_3_bc76_alt	sample_count_3_bc77_alt	sample_count_3_bc78_alt	sample_count_3_bc79_alt
variant_10	7	7	3	1	15	1	18	43	2	22	16	16	4	6	3	17	2	24	3	17	5	16	41	8	12	25	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	29	5	12	11	3	2	4	2	2	1	4	32	10	2	5	16	6	8	12	8	9	7	13	4	8	4	2	11	1	16	9	8	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	2	6	1	7	8	2	24	8	3	23	4	7	1	2	13	11	1	4	14	1	4	2	6	10	10	8	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	27	10	2	32	3	16	35	6	19	17	16	6	5	55	1	13	22	15	17	2	10	34	1	54	6	12	15	2	5	15	11	44	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	10	22	7	4	4	13	2	31	5	15	27	6	12	49	6	8	12	13	15	7	12	5	5	21	1	23	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	25	35	17	3	2	18	3	10	14	13	25	25	18	16	10	25	18	2	10	19	2	8	4	27	7	1	10	12	7	15	40	19	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
variant_100	39	9	21	16	2	5	22	46	23	55	38	23	39	13	21	2	8	31	27	32	5	7	9	19	20	7	14	16	45	1	36	14	7	14	8	3	26	11	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	4	6	11	1	19	2	7	3	31	6	3	4	2	1	13	2	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	8	18	12	39	12	15	5	22	17	24	39	20	5	17	30	5	8	23	20	58	18	1	10	2	12	7	8	11	6	13	17	22	64	23	20	11	6	10	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	11	8	19	11	13	6	5	2	9	20	11	7	1	4	3	21	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	13	25	19	43	3	41	10	51	3	26	49	8	27	3	5	21	36	5	42	5	10	2	2	26	7	29	2	33	5	5	15	36	115	5	37	4	7	27	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	3	9	32	27	8	18	4	6	11	3	9	5	4	1	3	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
variant_100314	1	17	3	6	8	4	4	6	15	12	4	17	7	10	9	11	15	9	16	2	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	5	5	20	11	9	4	2	6	24	5	11	12	3	10	11	2	4	6	29	34	4	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	3	2	18	11	21	6	1	7	33	10	3	38	2	6	6	2	5	2	2	28	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
variant_100463	1	2	3	11	2	2	24	3	9	1	2	4	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	3	4	1	4	1	4	9	2	7	8	2	14	10	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	22	1	9	2	2	2	6	8	3	9	4	6	4	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
variant_101	7	19	4	28	1	5	1	1	9	1	6	7	5	12	59	13	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	32	2	12	1	22	19	11	6	45	8	13	2	24	8	51	12	16	4	51	11	25	35	7	6	79	34	19	9	26	4	43	10	11	6	4	18	7	22	1	37	6	58	2	12	41	25	2	16	17	29	19	20	63	16	82	15	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	12	40	3	16	23	5	3	2	2	6	4	12	5	24	26	8	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	48	23	39	29	5	84	37	51	27	18	24	20	20	15	13	13	18	6	32	9	23	30	8	38	22	12	49	23	40	6	13	9	32	20	38	5	4	25	31	4	39	5	58	36	16	23	5	61	1	22	4	5	272	8	37	23	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	21	5	5	3	4	2	4	3	1	2	2	2	16	12	3	6	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	32	1	37	22	33	45	14	1	23	36	22	5	11	5	53	17	14	10	2	2	22	11	14	62	12	25	6	17	62	7	91	10	25	9	6	1	11	15	58	23	12	24	2	12	106	19	35	51	16	13	26	27	88	28	80	3	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
variant_101165	4	13	9	26	13	2	24	2	5	22	4	2	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	2	3	3	10	4	2	13	1	27	2	3	7	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	5	1	12	7	3	1	4	3	6	12	7	3	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA

Now we create the MPRAset used as input to BCalm.

# create the variant specific MPRAset
BcVariantMPRASetExample <- MPRASet(DNA = dna_var, RNA = rna_var, eid = row.names(dna_var), barcode = NULL)

2.2 Element testing

The dataset is the same one we used above, but we have to add labels to the data to distinguish between control and test groups, thus allowing us to easily identify and compare these different groups in the analysis later.

data(LabelExample)
table(LabelExample)

## LabelExample
## control  tested 
##     198    1475

kable(head(LabelExample), "html") %>% kable_styling("striped") %>% scroll_box(width = "100%")

	x
oligo_000702	tested
oligo_000703	tested
oligo_000706	tested
oligo_000707	tested
oligo_000711	tested
oligo_000713	tested

Once again, we perform downsampling on this dataset using the downsample_barcodes function.

elem_df <- downsample_barcodes(BcSetExample)

As before, we use create_dna_df and create_rna_df to format the data correctly for the MPRASet function. However, this time we specify id_column_name = "name" since the default, id_column_name = "variant_id", does not match our data format.

dna_elem <- create_dna_df(elem_df, id_column_name="name")
rna_elem <- create_rna_df(elem_df, id_column_name="name")

To compare between test and control, we need to add the labels to the MPRASet.

BcLabelMPRASetExample <- MPRASet(DNA = dna_elem, RNA = rna_elem, eid = row.names(dna_elem), barcode = NULL, label=LabelExample)

With the data prepared and preprocessed, we now have the foundation to conduct our analysis.

3 Analysis

In this section we get to see the usage of the mpralm and the fit_elements functions. We take the MPRASet created in the preprocessing chapter. BCalm allows us to analyze individual barcode counts as separate samples, capturing additional data variation and potentially increasing statistical power.

3.1 Variant Analysis

We will start with variant testing. In order to achieve this, we employ the mpralm function. Which column belongs to which replicate is described in a blocking vector, also used to normalize the counts per replicate. The design matrix gives information which count comes from the reference and which from the alternative allele.

bcs <- ncol(dna_var) / nr_reps
design <- data.frame(intcpt = 1, alt = grepl("alt", colnames(BcVariantMPRASetExample)))
block_vector <- rep(1:nr_reps, each=bcs)
mpralm_fit_var <- mpralm(object = BcVariantMPRASetExample, design = design, aggregate = "none", normalize = TRUE, model_type = "corr_groups", plot = FALSE, block = block_vector)

top_var <- topTable(mpralm_fit_var, coef = 2, number = Inf)
kable(head(rna_var), "html") %>% kable_styling("striped") %>% scroll_box(width = "100%")

	sample_count_1_bc1_ref	sample_count_1_bc2_ref	sample_count_1_bc3_ref	sample_count_1_bc4_ref	sample_count_1_bc5_ref	sample_count_1_bc6_ref	sample_count_1_bc7_ref	sample_count_1_bc8_ref	sample_count_1_bc9_ref	sample_count_1_bc10_ref	sample_count_1_bc11_ref	sample_count_1_bc12_ref	sample_count_1_bc13_ref	sample_count_1_bc14_ref	sample_count_1_bc15_ref	sample_count_1_bc16_ref	sample_count_1_bc17_ref	sample_count_1_bc18_ref	sample_count_1_bc19_ref	sample_count_1_bc20_ref	sample_count_1_bc21_ref	sample_count_1_bc22_ref	sample_count_1_bc23_ref	sample_count_1_bc24_ref	sample_count_1_bc25_ref	sample_count_1_bc26_ref	sample_count_1_bc27_ref	sample_count_1_bc28_ref	sample_count_1_bc29_ref	sample_count_1_bc30_ref	sample_count_1_bc31_ref	sample_count_1_bc32_ref	sample_count_1_bc33_ref	sample_count_1_bc34_ref	sample_count_1_bc35_ref	sample_count_1_bc36_ref	sample_count_1_bc37_ref	sample_count_1_bc38_ref	sample_count_1_bc39_ref	sample_count_1_bc40_ref	sample_count_1_bc41_ref	sample_count_1_bc42_ref	sample_count_1_bc43_ref	sample_count_1_bc44_ref	sample_count_1_bc45_ref	sample_count_1_bc46_ref	sample_count_1_bc47_ref	sample_count_1_bc48_ref	sample_count_1_bc49_ref	sample_count_1_bc50_ref	sample_count_1_bc51_ref	sample_count_1_bc52_ref	sample_count_1_bc53_ref	sample_count_1_bc54_ref	sample_count_1_bc55_ref	sample_count_1_bc56_ref	sample_count_1_bc57_ref	sample_count_1_bc58_ref	sample_count_1_bc59_ref	sample_count_1_bc60_ref	sample_count_1_bc61_ref	sample_count_1_bc62_ref	sample_count_1_bc63_ref	sample_count_1_bc64_ref	sample_count_1_bc65_ref	sample_count_1_bc66_ref	sample_count_1_bc67_ref	sample_count_1_bc68_ref	sample_count_1_bc69_ref	sample_count_1_bc70_ref	sample_count_1_bc71_ref	sample_count_1_bc72_ref	sample_count_1_bc73_ref	sample_count_1_bc74_ref	sample_count_1_bc75_ref	sample_count_1_bc76_ref	sample_count_1_bc77_ref	sample_count_1_bc78_ref	sample_count_1_bc79_ref	sample_count_1_bc1_alt	sample_count_1_bc2_alt	sample_count_1_bc3_alt	sample_count_1_bc4_alt	sample_count_1_bc5_alt	sample_count_1_bc6_alt	sample_count_1_bc7_alt	sample_count_1_bc8_alt	sample_count_1_bc9_alt	sample_count_1_bc10_alt	sample_count_1_bc11_alt	sample_count_1_bc12_alt	sample_count_1_bc13_alt	sample_count_1_bc14_alt	sample_count_1_bc15_alt	sample_count_1_bc16_alt	sample_count_1_bc17_alt	sample_count_1_bc18_alt	sample_count_1_bc19_alt	sample_count_1_bc20_alt	sample_count_1_bc21_alt	sample_count_1_bc22_alt	sample_count_1_bc23_alt	sample_count_1_bc24_alt	sample_count_1_bc25_alt	sample_count_1_bc26_alt	sample_count_1_bc27_alt	sample_count_1_bc28_alt	sample_count_1_bc29_alt	sample_count_1_bc30_alt	sample_count_1_bc31_alt	sample_count_1_bc32_alt	sample_count_1_bc33_alt	sample_count_1_bc34_alt	sample_count_1_bc35_alt	sample_count_1_bc36_alt	sample_count_1_bc37_alt	sample_count_1_bc38_alt	sample_count_1_bc39_alt	sample_count_1_bc40_alt	sample_count_1_bc41_alt	sample_count_1_bc42_alt	sample_count_1_bc43_alt	sample_count_1_bc44_alt	sample_count_1_bc45_alt	sample_count_1_bc46_alt	sample_count_1_bc47_alt	sample_count_1_bc48_alt	sample_count_1_bc49_alt	sample_count_1_bc50_alt	sample_count_1_bc51_alt	sample_count_1_bc52_alt	sample_count_1_bc53_alt	sample_count_1_bc54_alt	sample_count_1_bc55_alt	sample_count_1_bc56_alt	sample_count_1_bc57_alt	sample_count_1_bc58_alt	sample_count_1_bc59_alt	sample_count_1_bc60_alt	sample_count_1_bc61_alt	sample_count_1_bc62_alt	sample_count_1_bc63_alt	sample_count_1_bc64_alt	sample_count_1_bc65_alt	sample_count_1_bc66_alt	sample_count_1_bc67_alt	sample_count_1_bc68_alt	sample_count_1_bc69_alt	sample_count_1_bc70_alt	sample_count_1_bc71_alt	sample_count_1_bc72_alt	sample_count_1_bc73_alt	sample_count_1_bc74_alt	sample_count_1_bc75_alt	sample_count_1_bc76_alt	sample_count_1_bc77_alt	sample_count_1_bc78_alt	sample_count_1_bc79_alt	sample_count_2_bc1_ref	sample_count_2_bc2_ref	sample_count_2_bc3_ref	sample_count_2_bc4_ref	sample_count_2_bc5_ref	sample_count_2_bc6_ref	sample_count_2_bc7_ref	sample_count_2_bc8_ref	sample_count_2_bc9_ref	sample_count_2_bc10_ref	sample_count_2_bc11_ref	sample_count_2_bc12_ref	sample_count_2_bc13_ref	sample_count_2_bc14_ref	sample_count_2_bc15_ref	sample_count_2_bc16_ref	sample_count_2_bc17_ref	sample_count_2_bc18_ref	sample_count_2_bc19_ref	sample_count_2_bc20_ref	sample_count_2_bc21_ref	sample_count_2_bc22_ref	sample_count_2_bc23_ref	sample_count_2_bc24_ref	sample_count_2_bc25_ref	sample_count_2_bc26_ref	sample_count_2_bc27_ref	sample_count_2_bc28_ref	sample_count_2_bc29_ref	sample_count_2_bc30_ref	sample_count_2_bc31_ref	sample_count_2_bc32_ref	sample_count_2_bc33_ref	sample_count_2_bc34_ref	sample_count_2_bc35_ref	sample_count_2_bc36_ref	sample_count_2_bc37_ref	sample_count_2_bc38_ref	sample_count_2_bc39_ref	sample_count_2_bc40_ref	sample_count_2_bc41_ref	sample_count_2_bc42_ref	sample_count_2_bc43_ref	sample_count_2_bc44_ref	sample_count_2_bc45_ref	sample_count_2_bc46_ref	sample_count_2_bc47_ref	sample_count_2_bc48_ref	sample_count_2_bc49_ref	sample_count_2_bc50_ref	sample_count_2_bc51_ref	sample_count_2_bc52_ref	sample_count_2_bc53_ref	sample_count_2_bc54_ref	sample_count_2_bc55_ref	sample_count_2_bc56_ref	sample_count_2_bc57_ref	sample_count_2_bc58_ref	sample_count_2_bc59_ref	sample_count_2_bc60_ref	sample_count_2_bc61_ref	sample_count_2_bc62_ref	sample_count_2_bc63_ref	sample_count_2_bc64_ref	sample_count_2_bc65_ref	sample_count_2_bc66_ref	sample_count_2_bc67_ref	sample_count_2_bc68_ref	sample_count_2_bc69_ref	sample_count_2_bc70_ref	sample_count_2_bc71_ref	sample_count_2_bc72_ref	sample_count_2_bc73_ref	sample_count_2_bc74_ref	sample_count_2_bc75_ref	sample_count_2_bc76_ref	sample_count_2_bc77_ref	sample_count_2_bc78_ref	sample_count_2_bc79_ref	sample_count_2_bc1_alt	sample_count_2_bc2_alt	sample_count_2_bc3_alt	sample_count_2_bc4_alt	sample_count_2_bc5_alt	sample_count_2_bc6_alt	sample_count_2_bc7_alt	sample_count_2_bc8_alt	sample_count_2_bc9_alt	sample_count_2_bc10_alt	sample_count_2_bc11_alt	sample_count_2_bc12_alt	sample_count_2_bc13_alt	sample_count_2_bc14_alt	sample_count_2_bc15_alt	sample_count_2_bc16_alt	sample_count_2_bc17_alt	sample_count_2_bc18_alt	sample_count_2_bc19_alt	sample_count_2_bc20_alt	sample_count_2_bc21_alt	sample_count_2_bc22_alt	sample_count_2_bc23_alt	sample_count_2_bc24_alt	sample_count_2_bc25_alt	sample_count_2_bc26_alt	sample_count_2_bc27_alt	sample_count_2_bc28_alt	sample_count_2_bc29_alt	sample_count_2_bc30_alt	sample_count_2_bc31_alt	sample_count_2_bc32_alt	sample_count_2_bc33_alt	sample_count_2_bc34_alt	sample_count_2_bc35_alt	sample_count_2_bc36_alt	sample_count_2_bc37_alt	sample_count_2_bc38_alt	sample_count_2_bc39_alt	sample_count_2_bc40_alt	sample_count_2_bc41_alt	sample_count_2_bc42_alt	sample_count_2_bc43_alt	sample_count_2_bc44_alt	sample_count_2_bc45_alt	sample_count_2_bc46_alt	sample_count_2_bc47_alt	sample_count_2_bc48_alt	sample_count_2_bc49_alt	sample_count_2_bc50_alt	sample_count_2_bc51_alt	sample_count_2_bc52_alt	sample_count_2_bc53_alt	sample_count_2_bc54_alt	sample_count_2_bc55_alt	sample_count_2_bc56_alt	sample_count_2_bc57_alt	sample_count_2_bc58_alt	sample_count_2_bc59_alt	sample_count_2_bc60_alt	sample_count_2_bc61_alt	sample_count_2_bc62_alt	sample_count_2_bc63_alt	sample_count_2_bc64_alt	sample_count_2_bc65_alt	sample_count_2_bc66_alt	sample_count_2_bc67_alt	sample_count_2_bc68_alt	sample_count_2_bc69_alt	sample_count_2_bc70_alt	sample_count_2_bc71_alt	sample_count_2_bc72_alt	sample_count_2_bc73_alt	sample_count_2_bc74_alt	sample_count_2_bc75_alt	sample_count_2_bc76_alt	sample_count_2_bc77_alt	sample_count_2_bc78_alt	sample_count_2_bc79_alt	sample_count_3_bc1_ref	sample_count_3_bc2_ref	sample_count_3_bc3_ref	sample_count_3_bc4_ref	sample_count_3_bc5_ref	sample_count_3_bc6_ref	sample_count_3_bc7_ref	sample_count_3_bc8_ref	sample_count_3_bc9_ref	sample_count_3_bc10_ref	sample_count_3_bc11_ref	sample_count_3_bc12_ref	sample_count_3_bc13_ref	sample_count_3_bc14_ref	sample_count_3_bc15_ref	sample_count_3_bc16_ref	sample_count_3_bc17_ref	sample_count_3_bc18_ref	sample_count_3_bc19_ref	sample_count_3_bc20_ref	sample_count_3_bc21_ref	sample_count_3_bc22_ref	sample_count_3_bc23_ref	sample_count_3_bc24_ref	sample_count_3_bc25_ref	sample_count_3_bc26_ref	sample_count_3_bc27_ref	sample_count_3_bc28_ref	sample_count_3_bc29_ref	sample_count_3_bc30_ref	sample_count_3_bc31_ref	sample_count_3_bc32_ref	sample_count_3_bc33_ref	sample_count_3_bc34_ref	sample_count_3_bc35_ref	sample_count_3_bc36_ref	sample_count_3_bc37_ref	sample_count_3_bc38_ref	sample_count_3_bc39_ref	sample_count_3_bc40_ref	sample_count_3_bc41_ref	sample_count_3_bc42_ref	sample_count_3_bc43_ref	sample_count_3_bc44_ref	sample_count_3_bc45_ref	sample_count_3_bc46_ref	sample_count_3_bc47_ref	sample_count_3_bc48_ref	sample_count_3_bc49_ref	sample_count_3_bc50_ref	sample_count_3_bc51_ref	sample_count_3_bc52_ref	sample_count_3_bc53_ref	sample_count_3_bc54_ref	sample_count_3_bc55_ref	sample_count_3_bc56_ref	sample_count_3_bc57_ref	sample_count_3_bc58_ref	sample_count_3_bc59_ref	sample_count_3_bc60_ref	sample_count_3_bc61_ref	sample_count_3_bc62_ref	sample_count_3_bc63_ref	sample_count_3_bc64_ref	sample_count_3_bc65_ref	sample_count_3_bc66_ref	sample_count_3_bc67_ref	sample_count_3_bc68_ref	sample_count_3_bc69_ref	sample_count_3_bc70_ref	sample_count_3_bc71_ref	sample_count_3_bc72_ref	sample_count_3_bc73_ref	sample_count_3_bc74_ref	sample_count_3_bc75_ref	sample_count_3_bc76_ref	sample_count_3_bc77_ref	sample_count_3_bc78_ref	sample_count_3_bc79_ref	sample_count_3_bc1_alt	sample_count_3_bc2_alt	sample_count_3_bc3_alt	sample_count_3_bc4_alt	sample_count_3_bc5_alt	sample_count_3_bc6_alt	sample_count_3_bc7_alt	sample_count_3_bc8_alt	sample_count_3_bc9_alt	sample_count_3_bc10_alt	sample_count_3_bc11_alt	sample_count_3_bc12_alt	sample_count_3_bc13_alt	sample_count_3_bc14_alt	sample_count_3_bc15_alt	sample_count_3_bc16_alt	sample_count_3_bc17_alt	sample_count_3_bc18_alt	sample_count_3_bc19_alt	sample_count_3_bc20_alt	sample_count_3_bc21_alt	sample_count_3_bc22_alt	sample_count_3_bc23_alt	sample_count_3_bc24_alt	sample_count_3_bc25_alt	sample_count_3_bc26_alt	sample_count_3_bc27_alt	sample_count_3_bc28_alt	sample_count_3_bc29_alt	sample_count_3_bc30_alt	sample_count_3_bc31_alt	sample_count_3_bc32_alt	sample_count_3_bc33_alt	sample_count_3_bc34_alt	sample_count_3_bc35_alt	sample_count_3_bc36_alt	sample_count_3_bc37_alt	sample_count_3_bc38_alt	sample_count_3_bc39_alt	sample_count_3_bc40_alt	sample_count_3_bc41_alt	sample_count_3_bc42_alt	sample_count_3_bc43_alt	sample_count_3_bc44_alt	sample_count_3_bc45_alt	sample_count_3_bc46_alt	sample_count_3_bc47_alt	sample_count_3_bc48_alt	sample_count_3_bc49_alt	sample_count_3_bc50_alt	sample_count_3_bc51_alt	sample_count_3_bc52_alt	sample_count_3_bc53_alt	sample_count_3_bc54_alt	sample_count_3_bc55_alt	sample_count_3_bc56_alt	sample_count_3_bc57_alt	sample_count_3_bc58_alt	sample_count_3_bc59_alt	sample_count_3_bc60_alt	sample_count_3_bc61_alt	sample_count_3_bc62_alt	sample_count_3_bc63_alt	sample_count_3_bc64_alt	sample_count_3_bc65_alt	sample_count_3_bc66_alt	sample_count_3_bc67_alt	sample_count_3_bc68_alt	sample_count_3_bc69_alt	sample_count_3_bc70_alt	sample_count_3_bc71_alt	sample_count_3_bc72_alt	sample_count_3_bc73_alt	sample_count_3_bc74_alt	sample_count_3_bc75_alt	sample_count_3_bc76_alt	sample_count_3_bc77_alt	sample_count_3_bc78_alt	sample_count_3_bc79_alt
variant_10	7	7	3	1	15	1	18	43	2	22	16	16	4	6	3	17	2	24	3	17	5	16	41	8	12	25	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	29	5	12	11	3	2	4	2	2	1	4	32	10	2	5	16	6	8	12	8	9	7	13	4	8	4	2	11	1	16	9	8	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	2	6	1	7	8	2	24	8	3	23	4	7	1	2	13	11	1	4	14	1	4	2	6	10	10	8	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	27	10	2	32	3	16	35	6	19	17	16	6	5	55	1	13	22	15	17	2	10	34	1	54	6	12	15	2	5	15	11	44	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	10	22	7	4	4	13	2	31	5	15	27	6	12	49	6	8	12	13	15	7	12	5	5	21	1	23	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	25	35	17	3	2	18	3	10	14	13	25	25	18	16	10	25	18	2	10	19	2	8	4	27	7	1	10	12	7	15	40	19	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
variant_100	39	9	21	16	2	5	22	46	23	55	38	23	39	13	21	2	8	31	27	32	5	7	9	19	20	7	14	16	45	1	36	14	7	14	8	3	26	11	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	4	6	11	1	19	2	7	3	31	6	3	4	2	1	13	2	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	8	18	12	39	12	15	5	22	17	24	39	20	5	17	30	5	8	23	20	58	18	1	10	2	12	7	8	11	6	13	17	22	64	23	20	11	6	10	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	11	8	19	11	13	6	5	2	9	20	11	7	1	4	3	21	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	13	25	19	43	3	41	10	51	3	26	49	8	27	3	5	21	36	5	42	5	10	2	2	26	7	29	2	33	5	5	15	36	115	5	37	4	7	27	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	3	9	32	27	8	18	4	6	11	3	9	5	4	1	3	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
variant_100314	1	17	3	6	8	4	4	6	15	12	4	17	7	10	9	11	15	9	16	2	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	5	5	20	11	9	4	2	6	24	5	11	12	3	10	11	2	4	6	29	34	4	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	3	2	18	11	21	6	1	7	33	10	3	38	2	6	6	2	5	2	2	28	1	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
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variant_101	7	19	4	28	1	5	1	1	9	1	6	7	5	12	59	13	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	32	2	12	1	22	19	11	6	45	8	13	2	24	8	51	12	16	4	51	11	25	35	7	6	79	34	19	9	26	4	43	10	11	6	4	18	7	22	1	37	6	58	2	12	41	25	2	16	17	29	19	20	63	16	82	15	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	12	40	3	16	23	5	3	2	2	6	4	12	5	24	26	8	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	48	23	39	29	5	84	37	51	27	18	24	20	20	15	13	13	18	6	32	9	23	30	8	38	22	12	49	23	40	6	13	9	32	20	38	5	4	25	31	4	39	5	58	36	16	23	5	61	1	22	4	5	272	8	37	23	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	21	5	5	3	4	2	4	3	1	2	2	2	16	12	3	6	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	32	1	37	22	33	45	14	1	23	36	22	5	11	5	53	17	14	10	2	2	22	11	14	62	12	25	6	17	62	7	91	10	25	9	6	1	11	15	58	23	12	24	2	12	106	19	35	51	16	13	26	27	88	28	80	3	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA
variant_101165	4	13	9	26	13	2	24	2	5	22	4	2	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	2	3	3	10	4	2	13	1	27	2	3	7	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	5	1	12	7	3	1	4	3	6	12	7	3	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA	NA

ggplot(top_var, aes(x = logFC, y = -log10(P.Value))) +
  geom_point(alpha = 0.6)

3.2 Element Analysis

BCalm provides the function fit_elements. It takes the MPRASet object as input and applies the statistical modeling. Again the block_vector gives reference which barcode belongs to which replicate. We again set normalize = TRUE to perform total count normalization on the RNA and DNA libraries.

bcs <- ncol(dna_elem) / nr_reps
block_vector <- rep(1:nr_reps, each=bcs)
mpralm_fit_elem <- fit_elements(object = BcLabelMPRASetExample, normalize=TRUE, block = block_vector, plot = FALSE)

3.2.1 Visualisation and results

In this section, we will examine the visualization of our analysis results using the mpra_treat and plot_groups functions. To visualize our results, we utilize the plot_groups function, which allows us to compare logratios for each group. We use the results from fit_elements above. As negative controls we use "control" and as test "tested".

plot_groups(mpralm_fit_elem, 0.975, neg_label="control", test_label="tested")

The mpra_treat() function reimplements the treat() function from the limma package. This function performs a t-test with a specified threshold, making it especially useful for identifying elements with significant differential activity in MPRA data.

treat <- mpra_treat(mpralm_fit_elem, 0.975, neg_label="control")
result <- topTreat(treat, coef = 1, number = Inf)
head(result)

##                 logFC  AveExpr        t       P.Value     adj.P.Val
## oligo_006626 3.780354 3.783778 34.48748 1.908268e-137 3.192533e-134
## oligo_006624 3.528993 3.532478 28.82343 1.179753e-107 9.868637e-105
## oligo_006203 2.900044 2.902953 16.70435  1.642477e-48  9.159546e-46
## oligo_006468 2.215949 2.220075 16.16453  7.080540e-48  2.961436e-45
## oligo_005287 1.951758 1.954487 15.58402  1.340092e-45  4.483949e-43
## oligo_005641 1.820148 1.823736 14.10421  7.558722e-39  2.014197e-36

4 Session Info

R Under development (unstable) (2024-10-21 r87258) Platform: x86_64-pc-linux-gnu Running under: Ubuntu 24.04.1 LTS

Matrix products: default BLAS: /home/biocbuild/bbs-3.21-bioc/R/lib/libRblas.so LAPACK: /usr/lib/x86_64-linux-gnu/lapack/liblapack.so.3.12.0

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

time zone: America/New_York tzcode source: system (glibc)

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

other attached packages: [1] kableExtra_1.4.0 ggplot2_3.5.1
[3] dplyr_1.1.4 BCalm_0.99.0
[5] curl_6.1.0 limma_3.63.3
[7] SummarizedExperiment_1.37.0 Biobase_2.67.0
[9] GenomicRanges_1.59.1 GenomeInfoDb_1.43.2
[11] IRanges_2.41.2 S4Vectors_0.45.2
[13] MatrixGenerics_1.19.1 matrixStats_1.5.0
[15] BiocGenerics_0.53.3 generics_0.1.3
[17] BiocStyle_2.35.0

loaded via a namespace (and not attached): [1] gtable_0.3.6 xfun_0.50 bslib_0.8.0
[4] mpra_1.29.0 lattice_0.22-6 vctrs_0.6.5
[7] tools_4.5.0 tibble_3.2.1 pkgconfig_2.0.3
[10] Matrix_1.7-1 lifecycle_1.0.4 GenomeInfoDbData_1.2.13 [13] farver_2.1.2 compiler_4.5.0 stringr_1.5.1
[16] statmod_1.5.0 munsell_0.5.1 htmltools_0.5.8.1
[19] sass_0.4.9 yaml_2.3.10 pillar_1.10.1
[22] crayon_1.5.3 jquerylib_0.1.4 tidyr_1.3.1
[25] DelayedArray_0.33.3 cachem_1.1.0 abind_1.4-8
[28] tidyselect_1.2.1 digest_0.6.37 stringi_1.8.4
[31] purrr_1.0.2 bookdown_0.42 labeling_0.4.3
[34] fastmap_1.2.0 grid_4.5.0 colorspace_2.1-1
[37] cli_3.6.3 SparseArray_1.7.2 magrittr_2.0.3
[40] S4Arrays_1.7.1 withr_3.0.2 scales_1.3.0
[43] UCSC.utils_1.3.0 rmarkdown_2.29 XVector_0.47.2
[46] httr_1.4.7 evaluate_1.0.3 knitr_1.49
[49] viridisLite_0.4.2 rlang_1.1.4 glue_1.8.0
[52] xml2_1.3.6 BiocManager_1.30.25 svglite_2.1.3
[55] rstudioapi_0.17.1 jsonlite_1.8.9 R6_2.5.1
[58] systemfonts_1.1.0

References

Csárdi, Gábor, Jim Hester, Hadley Wickham, Winston Chang, Martin Morgan, and Dan Tenenbaum. 2024. “README — Cran.r-Project.org.” https://cran.r-project.org/web/packages/remotes/readme/README.html.

Gordon, M. Grace, Fumitaka Inoue, Beth Martin, Max Schubach, Vikram Agarwal, Sean Whalen, Shiyun Feng, et al. 2020. “lentiMPRA and MPRAflow for High-Throughput Functional Characterization of Gene Regulatory Elements.” Nature Protocols 15 (8): 2387–2412. https://doi.org/10.1038/s41596-020-0333-5.

Law, Charity W, Yunshun Chen, Wei Shi, and Gordon K Smyth. 2014. “Voom: Precision Weights Unlock Linear Model Analysis Tools for RNA-seq Read Counts.” Genome Biology 15: R29. https://doi.org/10.1186/gb-2014-15-2-r29.

Myint, Leslie, Dimitrios G Avramopoulos, Loyal A Goff, and Kasper D Hansen. 2019. “Linear Models Enable Powerful Differential Activity Analysis in Massively Parallel Reporter Assays.” BMC Genomics 20: 209. https://doi.org/10.1186/s12864-019-5556-x.

Wickham, Hadley, Jim Hester, Winston Chang, and Jennifer Bryan. 2022. Devtools: Tools to Make Developing r Packages Easier.

BCalm and analyze your MPRA data

January 13, 2025

Abstract

Package

Contents